# Publications

From ARO MURI

Publications

## Publications reporting on research supported by the ARO MURI on Adaptive Exploitation of Non-Commutative Multimodal Information Structure

**2016**

- Papers Published in Peer-Reviewed Journals

- V. Kostina and S. Verdu, "Nonasymptotic noisy lossy source coding," IEEE Transactions on Information Theory, vol. 62, no. 11, pp. 6111-6123, 2016.
- I. Sason and S. Verdu, "f-divergence inequalities," IEEE Transactions on Information Theory, vol. 62, no. 11, pp. 5973{6006, 2016.

- Peer-Reviewed Conference Proceedings Publications

- P.-Y. Chen, B. Zhang, M. Al Hasan, "Incremental Method for Spectral Clustering of Increasing Orders," 12th International Workshop on Mining and Learning with Graphs, San Francisco Aug. 2016.
- P.-Y. Chen, C.-C, Tu, P.-S. Ting, Y.-Y. Lo, D. Koutra and A.O. Hero, "Identifying Influential Links for Event Propagation on Twitter: A Network of Networks Approach," arXiv:1609.05378, Sep 2016.
- T.P. Coleman, J. Tantiongloc, A. Allegra, D. Mesa, D. Kang, and M. Mendoza, "Diffeomorphism learning via relative entropy constrained optimal transport," in Signal and Information Processing (GlobalSIP), 2016 IEEE Global Conference on. IEEE, 2016, pp. 1330-1334.
- K. Greenewald, S. Kelley, A.Hero, "Dynamic metric learning from pairwise comparisons," Allerton Conference on Communication, Control and Computing 2016.
- A. Jain, S.R. Kulkarni, and S. Verdu, "Energy efficiency of wireless cooperation," in Communication, Control, and Computing (Allerton), 2016 54th Annual Allerton Conference on. IEEE, 2016, pp. 664-671.
- A. Jain, A.R. Zamir, S. Savarese, and A. Saxena, "Structuralrnn: Deep learning on spatio-temporal graphs," in The IEEE Conference on Computer Vision and Pattern Recognition (CVPR), June 2016.
- W. Lu, V. Tarokh and A.O. Hero, "Analysis of a privacy-preserving PCA algorithm via random matrix theory," IEEE GlobalSIP Conference, Dec 2016.
- W. Lu, A.O. Hero and V. Tarokh, "Scaling laws and phase transitions for target detection in MIMO radar," IEEE Information Theory Workshop, Cambridge UK, 2016.
- S. Ravishankar, B.E. Moore, R.R. Nadakuditi, and J.A. Fessler, "Efficient learning of dictionaries with low-rank atoms," in Signal and Information Processing (GlobalSIP), 2016 IEEE Global Conference on. IEEE, 2016, pp. 222-226.
- S. Ravishankar, R.R. Nadakuditi, and J.A. Fessler, "Sum of outer products dictionary learning for inverse problems," in Signal and Information Processing (GlobalSIP), 2016 IEEE Global Conference on. IEEE, 2016, pp. 1142-1146.
- I. Sason and S. Verdu, "f-divergence inequalities via functional domination," in Science of Electrical Engineering (ICSEE), IEEE International Conference on the. IEEE, 2016, pp. 1-5.
- G. Vazquez-Vilar, A. Guill{\'e}n i F{\`a}bregas, and Sergio Verdu, "From the metaconverse bound to perfect codes," in International Conference on the Science of Electrical Engineering (ICSEE), 2016.
- M. Wilmanski, C. Kreucher, A.O. Hero, "Complex input convolutional neural networks for wide angle SAR ATR," IEEE GlobalSIP Conference, Dec 2016.
- H. Wu and R.R. Nadakuditi, "Free component analysis," in Signals, Systems and Computers, 2016 50th Asilomar Conference on. IEEE, 2016, pp. 85-89.

**2017**

- Papers Published in Peer-Reviewed Journals

- Y. Altmann, A. Maccarone, A. McCarthy, G. Newstadt, G.S. Buller, S. McLaughlin, and AO Hero, "Robust spectral unmixing of sparse multispectral lidar waveforms using gamma Markov random fields," IEEE Transactions on Computational Imaging, 3(4), pp.658-670, 2017.
- P.-Y. Chen and A.O. Hero, "Multilayer Spectral Graph Clustering via Convex Layer Aggregation: Theory and Algorithms," IEEE Tran. in Signal and Information Processing over Networks, vol. 3, no. 3 pp. 553-567, 2017. Arxiv:1609.07200
- H. Firouzi, B. Rajaratnam, A.O. Hero, "Two-stage Sampling, Prediction and Adaptive Regression via Correlation Screening (SPARCS)," IEEE Transactions on Information Theory, vol. 63, no. 1, pp. 698 - 714, Jan. 2017. https://arxiv.org/abs/1502:06189.
- K. Greenewald, S. Kelley, B. Oselio, A.O. Hero, "Similarity Function Tracking using Pairwise Comparisons," IEEE Transactions on Signal Processing, vol. 65, no. 21, pp. 5635-5648, 2017. arxiv:1610.03090.
- V. Kostina, Y. Polyanskiy, and S. Verdu, "Joint source-channel coding with feedback," IEEE Transactions on Information Theory, vol. 63, no. 6, pp. 3502-3515, 2017.
- J. Liu, P. Cuff, and S. Verdu, "E_$\gamma$-resolvability," IEEE Transactions on Information Theory, vol. 63, no. 5, pp. 2629-2658, 2017.
- S. Ravishankar, RR Nadakuditi, and JFessler, "Efficient sum of outer products dictionary learning (soup-dil) and its application to inverse problems," IEEE Transactions on Computational Imaging, 2017.
- S. Ravishankar, BE Moore, RR Nadakuditi, and JA Fessler, "Lowrank and adaptive sparse signal (lassi) models for highly accelerated dynamic imaging," IEEE Transactions on Medical Imaging, vol. 36, no. 5, pp. 1116-1128, 2017.
- I. Soloveychik, Y. Xiang, and V. Tarokh, "Pseudo-Wigner matrices," accepted in IEEE Transactions on Information Theory, arXiv:1701.05544, 2017.
- Justin Tantiongloc, Diego A Mesa, Rui Ma, Sanggyun Kim, Cristian H Alzate, Jaime J Camacho, Vidya Manian, and Todd P Coleman, "An information and control framework for optimizing user-compliant human-computer interfaces," Proceedings of the IEEE, vol. 105, no. 2, pp. 273-285, 2017.
- Anh Truong, S Rasoul Etesami, Jalal Etesami, and Negar Kiyavash, "Optimal attack strategies against predictors-learning from expert advice," IEEE Transactions on Information Forensics and Security, 2017.
- Wisler, A., Berisha, V., Spanias, A. and Hero, A.O., "Direct estimation of density functionals using a polynomial basis," IEEE Transactions on Signal Processing, 66(3), pp.558-572. 2017.

- Peer-Reviewed Conference Proceedings Publications

- AR Asadi, E. Abbe, and S. Verdu, "Compressing data on graphs with clusters," in Information Theory (ISIT), 2017 IEEE International Symposium on. IEEE, pp. 1583-1587,2017.
- A Bhargava, R Ganti, and R Nowak, "Active positive semidefinite matrix completion: Algorithms, theory and applications," in Artificial Intelligence and Statistics (AISTATS), pp. 1349-1357, 2017.
- S.P. Chepuri, S. Liu, G. Leus, and A.O. Hero, "Learning sparse graphs under smoothness prior," IEEE Conf on Acoustics, Speech and Signal Processing (ICASSP), New Orleans, Mar 2017.
- P.-Y. Chen and A.O. Hero, "AMOS: an automated model order selection algorithm for spectral graph clustering," IEEE Conf on Acoustics, Speech and Signal Processing (ICASSP), New Orleans, Mar 2017.
- TP Coleman, "Dynamical systems, ergodicity, and posterior matching," in Information Theory (ISIT), 2017 IEEE International Symposium on. IEEE, 2017, pp. 2678-2682.
- A. Ghassami and N. Kiyavash, "Interaction information for causal inference: The case of directed triangle," Proceedings of ISIT, June, 25-30, 2017, Aachen, Germany.
- Y. Kim and S. Verdu, "Fixed-length-parsing universal compression with side information," in Information Theory (ISIT), 2017 IEEE International Symposium on. IEEE, 2017, pp. 2563-2567
- J. Liu, R. van Handel, and S. Verdu, "Beyond the blowing-up lemma: Sharp converses via reverse hypercontractivity," in Information Theory (ISIT), 2017 IEEE International Symposium on. IEEE, 2017, pp. 943-947.
- S. Liu, S. P. Chepuri, G. Leus and A.O. Hero, "Distributed sensor selection for field estimation," Conf on Acoustics, Speech and Signal Processing (ICASSP), New Orleans, Mar 2017.
- S. Liu, P.-Y. Chen and A.O. Hero, "Distributed optimization for evolving networks of growing connectivity," IEEE Conf on Acoustics, Speech and Signal Processing (ICASSP), New Orleans, Mar 2017.
- K. Moon, S. Sekeh, M. Noshad and A.O. Hero, "Information theoretic structure learning with confidence," IEEE Conf on Acoustics, Speech and Signal Processing (ICASSP), New Orleans, Mar 2017. arXiv preprint arXiv:1609.03912.
- K. Moon, K. Sricharan, A.Hero, "Ensemble estimation of mutual information," Proceedings of the IEEE Intl Symp. on Information Theory (ISIT), Aachen, June 2017. arXiv preprint arXiv:1701.08083.
- K. Moon, K. Sricharan, A. Hero, "Ensemble Estimation of Distributional Functionals via k-Nearest Neighbors," Allerton Conference, 2017
- M. Noshad, S. Sekeh, K. Moon and A. Hero, "Direct Estimation of Information Divergence Using Nearest Neighbor Ratios," Proceedings of the IEEE Intl Symp. on Information Theory (ISIT), Aachen, June 2017. arXiv preprint arXiv:1702.05222.
- B. Oselio and A.O. Hero, "Dynamic reconstruction of influence graphs with adaptive directed information," IEEE Conf on Acoustics, Speech and Signal Processing (ICASSP), New Orleans, Mar 2017.
- D. Pimentel-Alarcon and R. Nowak, "Random consensus robust pca," in Artificial Intelligence and Statistics, 2017, pp. 344-352.
- S. Ravishankar and JA Fessler, "Data-driven models and approaches for imaging," in Mathematics in Imaging. Optical Society of America, 2017, pp. MW2C4.
- S. Salehkaleybar, J. Etesami, and N. Kiyavash, "Identifying nonlinear 1-step causal in uences in the presence of latent variables," Proceedings of ISIT, June, 25-30, 2017, Aachen, Germany.
- I. Sason and S. Verdu, "Arimoto-Renyi conditional entropy and bayesian hypothesis testing," in Information Theory (ISIT), 2017 IEEE International Symposium on. IEEE, 2017, pp. 2965-2969.
- Y. Shkel, M. Raginsky, and S. Verdu, "Universal lossy compression under logarithmic loss," in IEEE International Symposium on Information Theory, 2017.
- I. Soloveychik, Y. Xiang, and V. Tarokh, "Explicit symmetric pseudo-random matrices," Proceedings of ITW, November, 6-10, 2017, Kaohsiung, Taiwan.
- I. Soloveychik, Y. Xiang, and V. Tarokh, "On the spectral norms of pseudo-Wigner and related matrices," Proceedings of Allerton Conference, October, 4-6, 2017, University of Illinois at Urbana-Champaign.
- I. Soloveychik, Y. Xiang, and V. Tarokh, "Pseudo-Wigner matrices from dual bch codes," Proceedings of ISIT, June, 25-30, 2017, Aachen, Germany.
- S. Yagli, Y. Altug, and S. Verdu, "Minimax Renyi redundancy," Proceedings of ISIT, June, 25-30, 2017, Aachen, Germany, 2017.
- MH Yassaee, J. Liu, and S. Verdu, "One-shot multivariate covering lemmas via weighted sum and concentration inequalities," in Information Theory (ISIT), 2017 IEEE International Symposium on. IEEE, 2017, pp. 669-673.
- X. Wang, C. Jung, A. O Hero, "Part-Level Fully Convolutional Networks for Pedestrian Detection," IEEE Conf on Acoustics, Speech and Signal Processing (ICASSP), New Orleans, Mar 2017.

- Manuscripts (1)

- K. Greenewald, S. Zhou, A.O. Hero, "The Tensor Graphical Lasso (TeraLasso)," 2017 (Appeared in 2019 in JRSS-B). arxiv1705.03983.

**2018**

- Papers Published in Peer-Reviewed Journals

- Y. Altmann, S. McLaughlin, M.J. Padgett, V.K. Goyal, A.O. Hero, and D.Faccio, "Quantum-inspired computational imaging," Science, Vol. 361, Issue 6403, 17 Aug 2018. http://science.sciencemag.org/content/361/6403/eaat2298
- P.-Y. Chen and A. Hero, "Phase Transitions and a Model Order Selection Criterion for Spectral Graph Clustering," IEEE Trans on Signal Processing, Vol. 66 No. 13, pp. 3407 3420, July 2018.
- H.W. Chung, B.M> Sadler, L. Zheng and A.O. Hero, "Unequal error protection querying policies for the noisy 20 questions problem," IEEE Transactions on Information Theory, 64(2), pp.1105-1131, 2018.
- S. Liu, P.-Y. Chen and A. Hero, "Accelerated Distributed Dual Averaging over Evolving Networks of Growing Connectivity," IEEE Trans on Signal Processing. Vol. 66, No. 7, pp.1845-1859, July 2018.
- K.R. Moon, K. Sricharan, K. Greenewald, and A.O. Hero, "Ensemble Estimation of Information Divergence," Entropy (Special Issue on Information Theory for Machine Learning), vol. 20, no. 8, p. 560, July 2018. doi: 10.3390/e20080560.
- I. Soloveychik, Y. Xiang, and V. Tarokh, "Pseudo-Wigner matrices," IEEE Transactions on Information Theory, vol. 64, no. 4, pp. 31703178, 2018.
- I. Soloveychik, Y. Xiang, and V. Tarokh, "Symmetric pseudo-random matrices," IEEE Transactions on Information The- ory, vol. 64, no. 4, pp. 31793196, 2018.
- Sadeghian, A., Voisin, M., Legros, F., Vesel, R., Alahi, A., and Savarese, S., "Car-net: Clairvoyant attentive recurrent network," In Proceedings of the European Conference on Computer Vision (ECCV), pp. 151-167, 2018.
- Zamir, A. R., Sax, A., Shen, W., Guibas, L., Malik, J., and Savarese, S., "Taskonomy: Disentangling Task Transfer Learning," In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 3712-3722, 2018. Best Paper Award.

- Peer-Reviewed Conference Proceedings Publications

- T. Banerjee, G. Whipps, P. Gurram, V. Tarokh, "Sequential Event Detection Using Multimodal Data in Nonstationary Environments," in Proc. of the 21st International Conference on Information Fusion, July 2018.
- T. Banerjee, G. Whipps, P. Gurram, and V. Tarokh, "Cyclostationary statistical models and algorithms for anomaly detection using multi-modal data," Accepted to IEEE Global Conference on Signal and Information Processing (GlobalSIP), 2018. https://arxiv.org/abs/1807.06945.
- H.-W. Chung, B. Sadler, L. Zheng, A. Hero, "Unequal error protection querying policies for the noisy 20 questions problem," IEEE Conf on Acoustics, Speech and Signal Processing (ICASSP), Calgary, April 2018.
- H-.W. Chung, J-.O. Lee, D. Kim, A.O. Hero, "Trade-offs Between Query Difficulty and Sample Complexity in Crowdsourced Data Acquisition," 2018 56th Allerton Conference on Communication, Control, and Computing, Oct 2018.
- A. Ghassami, N. Kiyavash, B. Huang, K. Zhang, "Multi-domain causal structure learning in linear systems," In Advances in neural information processing systems, 2018.
- S. Liu, P.-Y. Chen, I. Rajapakse, A. Hero, "First-order bifurcation detection for dynamic complex networks," IEEE Conf on Acoustics, Speech and Signal Processing (ICASSP), Calgary, April 2018.
- S. Liu, P.-Y. Chen, J. Chen, and A. Hero, "Zeroth-Order Online Alternating Direction Method of Multipliers: Convergence Analysis and Applications," AISTATS 2018.
- M. Noshad and A. Hero, "Rate-optimal meta learning of classification error," IEEE Conf on Acoustics, Speech and Signal Processing (ICASSP), Calgary, April 2018.
- M. Noshad and A. Hero, "Scalable Hash-Based Estimation of Divergence Measures," AISTATS 2018.
- A Prasadan and RR Nadakuditi, "The finite sample performance of dynamic mode decomposition," To appear in IEEE GlobalSIP. pp. 286-290, IEEE, 2018.
- G. Schamberg and T.P. Coleman, "Quantifying Context-Dependent Causal Influences", NeurIPS Workshop on Causal Learning, December 2018.
- S. Sekeh, B. Oselio, A. Hero, "A Dimension-Independent discriminant between distributions," IEEE Conf on Acoustics, Speech and Signal Processing (ICASSP), Calgary, April 2018.
- S. Sekeh, B. Oselio, A. Hero, "Multi-class Bayes error estimation with a global minimal spanning tree," 2018 56th Allerton Conference on Communication, Control, and Computing, Oct 2018.

- Manuscripts (1)

- I. Soloveychik and V. Tarokh, "Asymptotically pseudo-free matrices," to be submitted to IEEE Transactions on Information Theory, 2018.

**2019**

- Papers Published in Peer-Reviewed Journals

- P.-Y. Chen, C.-C, Tu, P.-S. Ting, Y.-Y. Lo, D. Koutra and A.O. Hero, "Identifying Influential Links for Event Propagation on Twitter: A Network of Networks Approach," IEEE Trans on Signal and Information Processing over Networks, vol. 5, no. 1, pp. 139-151, Mar. 2019.
- K. Greenewald, S. Zhou, A.O. Hero, “The Tensor Graphical Lasso (TeraLasso),” Journal of the Royal Statistical Society, Series B, vol. 81, no. 5 Nov. 2019.
- D. A. Mesa, J. Tantiongloc, M. Mendoza, S. Kim, and T. P. Coleman, "A Distributed Framework for the Construction of Transport Maps," Neural Computation, April 2019 (Volume 31, Issue 4).
- D. A. Mesa, R. Ma, S. K. Gorantla and T. P. Coleman, "Construction and Analysis of Posterior Matching in Arbitrary Dimensions via Optimal Transport," IEEE Transactions on Information Theory, under review (minor revision), 2019.
- A. Prasadan, R. Nadakuditi, "Time Series Source Separation using Dynamic Mode Decomposition", SIAM Journal on Dynamical Systems, 2019. arXiv preprint arXiv:1903.01310,
- A. Prasadan, Arvind, Raj Rao Nadakuditi, and Debashis Paul. "Sparse equisigned PCA: Algorithms and performance bounds in the noisy rank-1 setting." Electronic Journal of Statistics 14.1 (2020): 345-385.
- A. Jung, A.O. Hero, A. Mara, S. Jahromi, A. Heimowitz, Y.C. Eldar, “Semi-supervised Learning in Network-Structured Data via Total Variation Minimization,” IEEE Trans. on Signal Processing, vol 67, no. 24 6256-6269, Dec. 2019.
- Mardia, J., Jiao, J., Tanczos, E., Nowak, R. D., and Weissman, T. “Concentration inequalities for the empirical distribution of discrete distributions: beyond the method of types,” Information and Inference: A Journal of the IMA, pp. 1-38, 2019.
- B. Moore, S. Ravishankar, R. R. Nadakuditi, and J. Fessler, "Online adaptive image reconstruction (OnAIR) using dictionary models," IEEE Transactions on Computational Imaging, 2019.
- B. Moore, C. Gao, R. R. Nadakuditi, "Panoramic Robust PCA for Foreground-Background Separation on Noisy, Free-Motion Camera Video," IEEE Transactions on Computational Imaging, vol. 5(2), pp. 195-211, 2019.
- M. Newman, X. Zhang and R. R. Nadakuditi, "Spectra of random networks with arbitrary degrees," Physical Review E, vol. 99(4), 042309, 2019.
- U. Oswal, A. Bhargava, and R. Nowak, "Linear Bandits with Feature Feedback," arXiv preprint arXiv:1903.03705 (2019).
- A. Prasadan and RR Nadakuditi, "Time Series Source Separation Using Dynamic Mode Decomposition." SIAM Journal on Applied Dynamical Systems 19.2 (2020): 1160-1199.
- G. Schamberg and TP Coleman, "Measuring Sample Path Causal Influences with Relative Entropy," IEEE Transactions on Information Theory, under review (minor revision), 2018.
- S. Sekeh and A. Hero, “Geometric estimation of multivariate dependency,” Entropy, vol. 21, no. 8, p. 787, Aug 2019. DOI 10.3390/e21040410.
- S. Sekeh, M. Noshad, A.O. Hero, “Convergence Rates for Empirical Estimation of Binary Classification Bounds,” Entropy, 21(12), 1144, Dec 2019
- Hao Wu and R. R. Nadakuditi, "Free component analysis," Jounral of Machine Learning Research, arXiv preprint arXiv:1905.017132019. Under review.
- L. Zhou and A. Hero, "Exponential Strong Converse for Successive Refinement with Causal Decoder Side Information," Entropy, vol. 21, no. 4, p. 410, April 2019.

- Peer-Reviewed Conference Proceedings Publications

- A. Ghassami, S. Salehkaleybar, N. Kiyavash, K. Zhang, "Counting and sampling from Markov equivalent DAGs using clique trees," In Proceedings of the AAAI Conference on Artificial Intelligence 2019.
- B. Jang and A.O. Hero, "Minimum volume topic modeling," AISTATS 2019, Japan. April 2019.
- K-S Jun, R Willett, S Wright, and R Nowak, "Bilinear Bandits with Low-rank Structure," In International Conference on Machine Learning, pp. 3163-3172. 2019
- V Kosaraju, A Sadeghian, R Martin-Martin, I Reid, H Rezatofighi, S Savarese, "Social-BiGAT: Multimodal Trajectory Forecasting using Bicycle-GAN and Graph Attention Networks," NeurIPS 2019, http://papers.neurips.cc/paper/8308-social-bigat-multimodal-trajectory-forecasting-using-bicycle-gan-and-graph-attention-networks.pdf.
- M. Noshad, Y. Zeng, AO Hero, "Scalable Mutual Information Estimation using Dependence Graphs," IEEE Conf. on Acoustics, Speech and Signal Processing (ICASSP), Brighton 2019.
- B. Oselio, A. Sadeghian, S. Savarese, AO Hero, "Time-varying interaction estimation using ensemble methods," IEEE Data Science Workshop, Minneapolis, May 2019.
- A. Pokle, R. Martin-Martin, P. Goebel, V. Chow, H. M. Ewald, J. Yang, Z. Wang, A. Sadeghian, D. Sadigh, S. Savarese, and M. Vazquez, "Deep local trajectory replanning and control for robot navigation," in 2019 International Conference on Robotics and Automation (ICRA), 2019, pp. 58155822.
- A Prasadan, A Lodhia and RR Nadakuditi, "Phase transitions in the dynamic mode decomposition algorithm," To appear in IEEE CAMSAP, IEEE, 2019.
- A Sadeghian, V Kosaraju, A Sadeghian, N Hirose, H Rezatofighi, and Silvio Savarese, "Sophie: An attentive gan for predicting paths compliant to social and phys- ical constraints," in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2019, pp. 13491358.
- G. Schamberg and T.P. Coleman, "On the Bias of Directed Information Estimators", IEEE International Symposium on Information Theory (ISIT), July 2019.
- S. Sekeh and A.O. Hero, "Feature Selection for multi-labeled variables via Dependency Maximization," IEEE Conf. on Acoustics, Speech and Signal Processing (ICASSP), Brighton 2019.
- H. Tiomoko Ali, S. Liu, Y. Yilmaz, AO Hero, R. Couillet, I. Rajapakse, "Latent heterogeneous multilayer community detection," IEEE Conf. on Acoustics, Speech and Signal Processing (ICASSP), Brighton 2019.

- Manuscripts

- R Martin-Martin, H Rezatofighi, A Shenoi, M Patel, J Gwak, N Dass, A Federman, P Goebel, S Savarese, "JRDB: A Dataset and Benchmark for Visual Perception for Navigation in Human Environments," arxiv, 2019, https://arxiv.org/abs/1910.11792.
- R. Nowak and E. Tanczos, “Tighter Confidence Intervals for Rating Systems,” arXiv, 2019, arXiv:1912.03528.

**2020**

- Papers Published in Peer-Reviewed Journals

- G. Schamberg and T.P. Coleman, "Measuring Sample Path Causal Influences with Relative Entropy", IEEE Transactions on Information Theory, Vol. 66, No. 5, May 2020. doi: 10.1109/TIT.2019.2945290
- G. Schamberg, W. Chapman, S. P. Xie, and T. P. Coleman, "Direct and Indirect Effects – An Information Theoretic Perspective", Entropy 2020, 22(8), 854; July 2020. doi: 10.3390/e22080854
- S. Sekeh, B. Oselio and A. Hero, “Learning to Bound the Multi-class Bayes Error,” IEEE Trans. on Signal Processing, IEEE Trans. on Signal Processing, vol. 68, pp. 3793 – 3807, May 2020. DOI 10.1109/TSP.2020.2994807. https://arxiv.org/abs/1811.06419.
- F. Xia, W.B. Shen, C. Li, P. Kasimbeg, M.E. Tchapmi, A. Toshev, R. Martín-Martín, and S. Savarese. "Interactive Gibson Benchmark: A Benchmark for Interactive Navigation in Cluttered Environments." IEEE Robotics and Automation Letters 5, no. 2 (2020): 713-720.
- M. Baranwal, Kunal Garg, Dimitra Panagou, A.O. Hero, “Distributed Fixed-Time Economic Dispatch under Time-Varying Topology and Uncertain Information,” IEEE Control Letters, Vol 5, Issue 4. pp. 1183-1188. Oct 2020. DOI 10.1109/LCSYS.2020.3020248.
- J LeBlanc, B Thelen and A Hero, “Testing that a local optimum of the likelihood is globally optimum using reparameterized embeddings,” Journal on Mathematical Imaging and Vision, 2020.

- Peer-Reviewed Conference Proceedings Publications

- L. Zhou and A. Hero, “Resolution Limits of Non-Adaptive Querying for Noisy 20 Questions Estimation,” IEEE Intl Symposium on Information Theory, Los Angeles, June 21-26, 2020, DOI: 10.1109/ISIT44484.2020.9174277.
- N. Charalambides, H. Madhavifar, A. Hero, “Numerically Stable Binary Gradient Coding,” IEEE Intl Symposium on Information Theory (ISIT), Los Angeles, Jan 2020.
- A. Magner, M. Baranwal and A. Hero, “The power of graph convolutional networks to distinguish random graph models,” IEEE Intl Symposium on Information Theory, Los Angeles, Jan 2020.
- E. Sabeti, P. Song, A. Hero, “Pattern-Based Analysis of Time Series: Estimation,” IEEE Intl Symposium on Information Theory, Los Angeles, Jan 2020.
- W. Yu, B. Jang, A. Hero, “The Sylvester Graphical Lasso,” AISTATS, May 2020. arxiv:2002.00288 https://arxiv.org/abs/2002.00288
- N. Charalambrides, M. Pilanci, A. Hero, “Weighted gradient coding with leverage score sampling,” IEEE Intl Conference on Acoustics Speech and Signal Processing, May 2020. arxiv:2002.02291 https://arxiv.org/abs/2002.02291.
- A. Raj, Y. Bresler, and B. Li, "Improving robustness of deep-learning-based image reconstruction," in 37th International Conference on Machine Learning, ICML, Online Conference, 2020. arXiv preprint arXiv:2002.11821 (2020).
- Y. Li and Y. Bresler, “Optimizing Optical Compressed Sensing for Multispectral DNN-Based Image Segmentation,” in Proc. 2020 Asilomar Conf. Signals, Systems, and Computers, Online, Nov. 2020, pp. 636–640. https://doi.org/10.1109/IEEECONF51394.2020.9443293

- Manuscripts

- B. Bordenave, S. Coste, and R.R. Nadakuditi. "Detection thresholds in very sparse matrix completion." arXiv preprint arXiv:2005.06062 (2020).
- K. Elkhalil, A. Hasan, J. Ding, S. Farsiu, and V. Tarokh, “Fisher auto-encoders,” arXiv preprint arXiv:2007.06120, 2020.
- A Magner, M. Baranwal, A.O. Hero, “Fundamental limitations of deep graph convolutional networks,” arxiv:1910.12954 May 2020.
- B. Mason, L. Jain, A. Tripathy, and R. Nowak, “Finding all${\epsilon}$-goodarms in stochastic bandits,”arXiv preprint arXiv:2006.08850, 2020.
- M. Malloy, A. Tripathy and R. Nowak, “Optimal Confidence Regions for the Multinomial Parameter,” arXiv, 2020, arXiv:2002.01044.
- C. Pérez-D'Arpino, C. Liu, P. Goebel, R. Martín-Martín, S. Savarese, "Robot Navigation in Constrained Pedestrian Environments using Reinforcement Learning," arxiv:2010.0860, 2020 https://arxiv.org/abs/2010.08600
- M. Soltani, Suya Wu, Jie Ding, and V. Tarokh, “Ped: Pruning with energy distance information,” arXiv preprint arXiv:2007.06121, 2020
- B. Tzen and M. Raginsky, ``A mean-field theory of lazy training in two-layer neural nets: entropic regularization and controlled McKean--Vlasov dynamics," arxiv:2002.01987, 2020.

**2021**

- Papers Published in Peer-Reviewed Journals

- Wang, Y, C. Hougen, B. Oselio, W. Dempsey, A. Hero, “A geometry-driven longitudinal topic model,” Harvard Data Science Review, April 30 2021.
- Robinson, B, R Malinas, Alfred Hero, “Space-Time Adaptive Detection at Low Sample Support,” accepted IEEE Trans, on Signal Processing, April 2021. arxiv.2010.03388.
- Noshad, M, J. Choi, Y. Sun, A. Hero, I. Dinov, “A Data Value Metric for Quantifying Information Content and Utility,” accepted Journal of Big Data, Mar. 2021.
- Zhou, L, and A. Hero, “Resolution Limits of Noisy 20 Questions Estimation,” IEEE Trans on Information Theory, Vol. 67, Issue 4, April 2021. DOI 10.1109/TIT.2021.3049796.
- Yilmaz, Y, M. Aktukmak and A. O. Hero, “Multimodal Data Fusion in High-Dimensional Heterogeneous Datasets Via Generative Models,” in IEEE Transactions on Signal Processing, vol. 69, pp. 5175-5188, 2021.
- Moon, K., K. Sricharan, A. Hero, “Ensemble Estimation of Generalized Mutual Information with Applications to Genomics,” IEEE Transactions on Information Theory, vol. 67, no. 9 pp. 5963-5996, 2021. arxiv:1701.08083.
- Baranwal, M, K Garg, D Panagou, A.O. Hero, “Distributed Fixed-Time Economic Dispatch under Time-Varying Topology and Uncertain Information,” IEEE Control Letters, vol. 5, no. 4, pp. 1183-1188, Oct. 2021.

- Peer-Reviewed Conference Proceedings Publications

- Wang, Y, A Hero, “SG-PALM: a Fast Physically Interpretable Tensor Graphical Model,” International Conference on Machine Learning (ICML), July 2021.
- Zhou, L, A Hero, “Achievable Resolution Limits for the Noisy Adaptive 20 Questions Problem,” IEEE International Symposium on Information Theory, July 2021.
- Zhou, L, A Hero, “Resolution Limits of Non-Adaptive 20 Questions Estimation for Multiple Targets,” IEEE International Symposium on Information Theory, July 2021.
- Sabeti, E, PXI Song and AO Hero, “Data discovery using lossless compression-based sparse representation,” IEEE ICASSP 2021. Arxiv:2103.08765 Mar 2021.
- Zhou, L and AO Hero, “Resolution Limits of 20 Questions Search Strategies for Moving Targets,” IEEE ICASSP 2021. Arxiv:2103.08097 Mar 2021.
- Charalambides, N, M. Palanci, and AO Hero, “Approximate Weighted CR Coded Matrix Multiplication,” IEEE ICASSP 2021. Arxiv:2011.09709 Nov 2020.
- Chen, K, J. K. Chen, J. Chuang, M. Vázquez, S. Savarese, “Topological Planning with Transformers for Vision-and-Language Navigation,” IEEE/CVF CVPR 2021. Arxiv:2012.05292 Dec 2020.
- Du, SS, W. Hu, Z. Li, R. Shen, Z. Song, J. Wu, “When is Particle Filtering Efficient for Planning in Partially Observed Linear Dynamical Systems?.” UAI 2021.
- Mohammadreza, S Wu, Suya, Li, Yuerong, Ravier, Robert, Ding, Jie and Tarokh, Vahid, Compressing Deep Networks Using Fisher Score of Feature Maps, 2021 Data Compression Conference (DCC).
- Elkhalil, K, A. Hasan, J. Ding, S. Farsiu and V. Tarokh, 2021 International Conference on Artificial Intelligence and Statistics (AISTATS)
- Coleman, TP and Maxim Raginsky, "Variational Bayesian inference and conditioned stochastic differential equations," invited paper IEEE Conference on Decision and Control (CDC), 2021.
- Zhou, L., Y. Wei, A. Hero, “Second-order asymptotically optimal outlying sequence detection with reject option,” IEEE Information Theory Workshop, Oct 2021.
- Hougen, C., L. Kaplan and A. Hero, “Uncertain Bayesian networks: learning from incomplete data,” IEEE Machine Learning for Signal Processing, Gold Coast Australia Oct 2021.
- Zhou, Linqi, Yilun Du, and Jiajun Wu. “3D shape generation and completion through point-voxel diffusion." In Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV), pp. 5826-5835. 2021.
- Li, Chengshu, Fei Xia, Roberto Martín-Martín, Michael Lingelbach, Sanjana Srivastava, Bokui Shen, Kent Elliott Vainio, Cem Gokmen, Gokul Dharan, Tanish Jain, Andrey Kurenkov, Karen Liu, Hyowon Gweon, Jiajun Wu, Li Fei-Fei, and Silvio Savarese. “iGibson 2.0: Object-Centric Simulation for Robot Learning of Everyday Household Tasks." In Conference on Robot Learning (CoRL), pp. 455-465. PMLR, 2021.
- Srivastava, Sanjana, Chengshu Li, Michael Lingelbach, Roberto Martín-Martín, Fei Xia, Kent Elliott Vainio, Zheng Lian, Cem Gokmen, Shyamal Buch, Karen Liu, Silvio Savarese, Hyowon Gweon, Jiajun Wu, and Li Fei-Fei. “BEHAVIOR: Benchmark for everyday household activities in virtual, interactive, and ecological environments." In Conference on Robot Learning (CoRL), pp. 477-490. PMLR, 2021.
- Gao, Ruohan, Yen-Yu Chang, Shivani Mall, Li Fei-Fei, and Jiajun Wu. “ObjectFolder: A Dataset of Objects with Implicit Visual, Auditory, and Tactile Representations." In Conference on Robot Learning (CoRL), pp. 466-476. PMLR, 2021.
- Elkhalil, K, A. Hasan, J. Ding, S. Farsiu, and V. Tarokh, “Fisher auto-encoders,” The International Conference on Artificial Intelligence and Statistics, vol. 130, pp. 352–360, 2021.
- Soltani, Mohammadreza, Suya Wu, Yuerong Li, Robert Ravier, Jie Ding, and Vahid Tarokh, “Compressing deep networks using fisher score of feature maps,” in 2021 Data Compression Conference (DCC). IEEE, 2021, pp. 371–371.

- Manuscripts

- Le, C.P, M. Soltani, R. Ravier, T. Standley, S. Savarese, V. Tarokh, "Neural Architecture Search From Fr\'echet Task Distance," Arxiv:2103.12827 Mar 2021.
- Iyer, Kritika and Najarian, Cyrus P and Fattah, Aya A and Arthurs, Christopher J and Soroushmehr, SM Reza and Subban, Vijayakumar and Sankardas, Mullasari A and Nadakuditi, Raj R and Nallamothu, Brahmajee K and Figueroa, C Alberto, "AngioNet: A Convolutional Neural Network for Vessel Segmentation in X-ray Angiography", https://doi.org/10.1101/2021.01.25.21250488, 2021
- Le, C.P., Soltani, Mohammadreza, Ravier, Robert, Standley, Trevor, Savarese, Silvio, Tarokh, Vahid, Neural Architecture Search From Fr$\backslash$'echet Task Distance, submitted.
- Tarzanagh, D, L Balzano, A Hero, “Fair structure learning in heterogeneous graphical models,” arxiv:2112.05128, 9 Dec 2021. Submitted
- Robinson, R, R. Malinas and A. Hero, “High-Dimensional Covariance Shrinkage for Signal Detection,” arxiv:2103.11830. 3 Dec 2021. Submitted.

**2022**

- Papers Published in Peer-Reviewed Journals

- Hero, A. B. Rajaratnam and Y. Wei, “A Unified Framework for Correlation Mining in Ultra-High Dimension,” arxiv:2101.04715. To appear in IEEE Trans. on Information Theory 2022.
- E Sabeti, S Oh, PX Song, A Hero. “A Pattern Dictionary Method for Anomaly Detection,” Entropy, vol 24, pp. 1095 Aug 2022.
- Magner, A, M Baranwal, A. Hero, “Fundamental limitations of deep graph convolutional networks,” the IEEE Trans. on Information Theory, vol 68, no 5, pp. 3218-3283, May 2022.
- Zhou, L, Y Wei, A Hero, “Second order asymptotically optimal outler hypothesis testing,” IEEE Trans. on Information Theory, vol. 68, no 6, June 2022.
- Wang, Y, Z. Sun, D. Song, A. Hero, “TensorGraphicalModels: A Julia Toolbox for Multiway Covariance Models and Ensemble Kalman Filter,” Software Impacts, May 14, 2022
- Le, Cat Phuoc, Mohammadreza Soltani, Juncheng Dong, and Vahid Tarokh, “Fisher task distance and its application in neural architecture search,” IEEE Access, vol. 10, pp. 1–1, 01 2022.
- Agrusa, A. S., Kunkel, D. C., Coleman, T., "Robust Regression and Optimal Transport Methods to Predict Gastrointestinal Disease Etiology from High Resolution EGG and Symptom Severity," IEEE Transactions on Biomedical Engineering, 2022
- Bordenave, Charles, Simon Coste, Raj Rao Nadakuditi, "Detection thresholds in very sparse matrix completion," Foundations of Computational Mathematics, 2022.

- Peer-Reviewed Conference Proceedings Publications

- Zhou, L Y Wei, A Hero, “Asymptotics for Outlier Hypothesis Testing ,” IEEE Intl Symposium on Information Theory (ISIT), Aalto Finland, June 2022.
- Charalambides, N, H Madhavifar, M Pilanci, A Hero, “Orthonormal Sketches for Secure Coded Regression,” IEEE Intl Symposium on Information Theory (ISIT), Aalto Finland, June 2022.
- Hougen, C, L Kaplan, M Ivanovska, F Cerutti, KV Mishra and A Hero, “SOLBP: Second-Order Loopy Belief Propagation for Inferencing in Uncertain Bayesian Networks,” 25th Conference on Information Fusion, Linkoping Sweden, July 2022.
- Jang, B, J. Nepper, M. Chevrette, Jo Handelsman and A.O. Hero, “High Dimensional Stochastic Linear Contextual Bandit with Missing Covariates,” IEEE Workshop on Machine Learning for Signal Processing (MLSP) Xian China, Aug. 2022.
- Robinson, B, R Malinas, V Latimer, B Morrison, A Hero, “An improvement on the Hotelling T2 test using the Ledoit-Wolf non-linear shrinkage estimator,” 30th European Conference on Signal Processing (EUSIPCO), Belgrade Serbia, to appear Sept. 2022.
- Wang, R, Yunzhi Zhang, Jiayuan Mao, Chin-Yi Cheng, and Jiajun Wu. “Translating a Visual LEGO Manual to a Machine-Executable Plan." In European Conference on Computer Vision (ECCV), 2022.
- Meng, C, Yutong He, Yang Song, Jiaming Song, Jiajun Wu, Jun-Yan Zhu, and Stefano Ermon. “SDEdit: Guided image synthesis and editing with stochastic differential equations." In International Conference on Learning Representations (ICLR). 2022.
- Mukherjee, Subhojyoti, Ardhendu S Tripathy, and Robert Nowak, “Chernoff sampling for active testing and extension to active regression,” in International Conference on Artificial Intelligence and Statistics. PMLR, 2022, pp. 7384–7432.
- Zhu, Yinglun, and Robert Nowak, “Pareto optimal model selection in linear bandits,” in International Conference on Artificial Intelligence and Statistics. PMLR, 2022, pp. 6793–6813.
- Le, Cat Phuoc, Juncheng Dong, Mohammadreza Soltani, and Vahid Tarokh, “Task affinity with maximum bipartite matching in few-shot learning,” in International Conference on Learning Representations, 2022.
- Habi, HV, H. Messer, and Y. Bresler, “A Generative Cramér-Rao Bound on Frequency Estimation with Learned Measurement Distribution,” in 2022 IEEE 12th Sensor Array and Multichannel Signal Processing Workshop (SAM), Jun. 2022, pp. 176–180. https://doi.org/10.1109/SAM53842.2022.9827830
- Coleman T.P. and Maxim Raginsky, “Variational bayesian inference and conditioned

stochastic differential equations,” in Proceedings of the IEEE Conference on Decision and Control, 2021.

- Manuscripts