Anandkumar, Anima (2023) Neural Operators for Solving PDEs and Inverse Design In: ISPD '23: Proceedings of the 2023 International Symposium on Physical Design; In: 2023 International Symposium on Physical Design (ISPD '23), 26-29 March 2023, Virtual Event https://doi.org/10.1145/3569052.3578911
Shi, Yuanyuan; Li, Zongyi et al. (2022) Machine Learning Accelerated PDE Backstepping Observers In: 2022 IEEE 61st Conference on Decision and Control (CDC); In: 2022 IEEE 61st Conference on Decision and Control (CDC), 6-9 December 2022, Cancun, Mexico https://doi.org/10.1109/cdc51059.2022.9992759
Jiang, Huaizu; Ma, Xiaojian et al. (2022) Bongard-HOI: Benchmarking Few-Shot Visual Reasoning for Human-Object Interactions In: 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR); In: 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 18-24 June 2022, New Orleans, LA https://doi.org/10.1109/cvpr52688.2022.01847
Wang, Xinlong; Yu, Zhiding et al. (2022) FreeSOLO: Learning to Segment Objects without Annotations In: 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR); In: 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 18-24 June 2022, New Orleans, LA https://doi.org/10.1109/cvpr52688.2022.01378
Elezi, Ismail; Yu, Zhiding et al. (2022) Not All Labels Are Equal: Rationalizing The Labeling Costs for Training Object Detection In: 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR); In: 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 18-24 June 2022, New Orleans, LA https://doi.org/10.1109/cvpr52688.2022.01409
Li, Zhiqi; Wang, Wenhai et al. (2022) Panoptic SegFormer: Delving Deeper into Panoptic Segmentation with Transformers In: 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR); In: 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 18-24 June 2022, New Orleans, LA https://doi.org/10.1109/cvpr52688.2022.00134
Shi, Yuanyuan; Qu, Guannan et al. (2022) Stability Constrained Reinforcement Learning for Real-Time Voltage Control In: 2022 American Control Conference (ACC); In: 2022 American Control Conference (ACC), 8-10 June 2022, Atlanta, GA https://doi.org/10.23919/acc53348.2022.9867476
Wong, Josiah; Makoviychuk, Viktor et al. (2022) OSCAR: Data-Driven Operational Space Control for Adaptive and Robust Robot Manipulation In: 2022 International Conference on Robotics and Automation (ICRA); In: 2022 International Conference on Robotics and Automation (ICRA), 23-27 May 2022, Philadelphia, PA https://doi.org/10.1109/icra46639.2022.9811967
Anandkumar, Anima (2022) ScaDL 2022 Invited Talk 3: Million-x speedups through convergence of AI and HPC In: 2022 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW); In: 2022 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW), 30 May-3 June 2022, Lyon, France https://doi.org/10.1109/ipdpsw55747.2022.00168
Lale, Sahin; Azizzadenesheli, Kamyar et al. (2021) Model Learning Predictive Control in Nonlinear Dynamical Systems In: 2021 60th IEEE Conference on Decision and Control (CDC); In: 2021 60th IEEE Conference on Decision and Control (CDC), 14-17 December 2021, Austin, TX https://doi.org/10.1109/cdc45484.2021.9683670
Sun, Jiachen; Cao, Yulong et al. (2021) Adversarially Robust 3D Point Cloud Recognition Using Self-Supervisions In: 35th Conference on Neural Information Processing Systems (NeurIPS 2021); In: 35th Conference on Neural Information Processing Systems (NeurIPS 2021), 6-14 December 2021, [Online Only] https://resolver.caltech.edu/CaltechAUTHORS:20221222-232011120
Yu, Zhiding; Huang, Rui et al. (2021) Coupled Segmentation and Edge Learning via Dynamic Graph Propagation In: 35th Conference on Neural Information Processing Systems (NeurIPS 2021); In: 35th Conference on Neural Information Processing Systems (NeurIPS 2021), 6-14 December 2021, [Online Only] https://resolver.caltech.edu/CaltechAUTHORS:20221222-225518550
Zhu, Chen; Ping, Wei et al. (2021) Long-Short Transformer: Efficient Transformers for Language and Vision In: Thirty-fifth Conference on Neural Information Processing Systems 35th Conference on Neural Information Processing Systems (NeurIPS 2021); In: 35th Conference on Neural Information Processing Systems (NeurIPS 2021), 6-14 December 2021, [Online Only] https://resolver.caltech.edu/CaltechAUTHORS:20221222-230911029
Xie, Enze; Wang, Wenhai et al. (2021) SegFormer: Simple and Efficient Design for Semantic Segmentation with Transformers In: Advances in Neural Information Processing Systems 34 (NeurIPS 2021); In: Advances in Neural Information Processing Systems 34 (NeurIPS 2021), 6-14 December 2021, Virtual Event https://resolver.caltech.edu/CaltechAUTHORS:20221222-232723221
Huang, Yujia; Zhang, Huan et al. (2021) Training Certifiably Robust Neural Networks with Efficient Local Lipschitz Bounds In: Advances in Neural Information Processing Systems 34 (NeurIPS 2021); arXiv; In: Advances in Neural Information Processing Systems 34 (NeurIPS 2021), 6-14 December 2021, Virtual Event https://resolver.caltech.edu/CaltechAUTHORS:20220714-224653496
Wang, Haotao; Xiao, Chaowei et al. (2021) AugMax: Adversarial Composition of Random Augmentations for Robust Training In: Advances in Neural Information Processing Systems 34; arXiv; In: Annual Conference on Neural Information Processing Systems 2021, NeurIPS 2021, 6-14 December 2021, Virtual Event https://resolver.caltech.edu/CaltechAUTHORS:20220714-224700672
Nie, Weili; Vahdat, Arash et al. (2021) Controllable and Compositional Generation with Latent-Space Energy-Based Models In: Advances in Neural Information Processing Systems 34 (NeurIPS 2021); arXiv; In: Advances in Neural Information Processing Systems 34 (NeurIPS 2021), 6-14 December 2021, Virtual Event https://resolver.caltech.edu/CaltechAUTHORS:20220714-224708055
Jeong, Yoonwoo; Ahn, Seokjun et al. (2021) Self-Calibrating Neural Radiance Fields In: 2021 IEEE/CVF International Conference on Computer Vision (ICCV); arXiv; In: 2021 IEEE/CVF International Conference on Computer Vision (ICCV), 10-17 October 2021, Montreal, QB https://doi.org/10.1109/ICCV48922.2021.00579
Lan, Shiyi; Yu, Zhiding et al. (2021) DiscoBox: Weakly Supervised Instance Segmentation and Semantic Correspondence from Box Supervision In: 2021 IEEE/CVF International Conference on Computer Vision (ICCV); arXiv; In: 2021 IEEE/CVF International Conference on Computer Vision (ICCV), 10-17 October 2021, Montreal, QB https://doi.org/10.1109/ICCV48922.2021.00339
Srikanth, Maya; Liu, Anqi et al. (2021) Dynamic Social Media Monitoring for Fast-Evolving Online Discussions In: Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data Mining; arXiv; In: 27th ACM SIGKDD Conference on Knowledge Discovery & Data Mining (KDD '21), 14-18 August 2021, Singapore https://doi.org/10.1145/3447548.3467171
Chrysos, Grigorios G.; Kossaifi, Jean et al. (2021) Unsupervised Controllable Generation with Self-Training In: 2021 International Joint Conference on Neural Networks (IJCNN); arXiv; In: 2021 International Joint Conference on Neural Networks (IJCNN), 18-22 July 2021, Shenzhen, China https://doi.org/10.1109/IJCNN52387.2021.9534045
Pan, Xinlei; Garg, Animesh et al. (2021) Emergent Hand Morphology and Control from Optimizing Robust Grasps of Diverse Objects In: 2021 IEEE International Conference on Robotics and Automation (ICRA); arXiv; In: 2021 IEEE International Conference on Robotics and Automation (ICRA), 30 May-5 June 2021, Xi'an, China https://doi.org/10.1109/ICRA48506.2021.9562092
Shi, Guanya; Zhu, Yifeng et al. (2021) Fast Uncertainty Quantification for Deep Object Pose Estimation In: 2021 IEEE International Conference on Robotics and Automation (ICRA); arXiv; In: 2021 IEEE International Conference on Robotics and Automation (ICRA), 30 May-5 June 2021, Xi'an, China https://doi.org/10.1109/ICRA48506.2021.9561483
Ravi Tej, Akella; Azizzadenesheli, Kamyar et al. (2021) Deep Bayesian Quadrature Policy Optimization In: Thirty-Fifth AAAI Conference on Artificial Intelligence (AAAI-21); arXiv; Vol. 35; Series Proceedings of the AAAI Conference on Artificial Intelligence; In: Thirty-Fifth AAAI Conference on Artificial Intelligence (AAAI-21), 2-9 February 2021, [Online Only] https://resolver.caltech.edu/CaltechAUTHORS:20201106-120212166
Lale, Sahin; Azizzadenesheli, Kamyar et al. (2021) Adaptive Control and Regret Minimization in Linear Quadratic Gaussian (LQG) Setting In: 2021 American Control Conference (ACC); arXiv; In: 2021 American Control Conference (ACC), 25-28 May 2021, New Orleans, LA https://doi.org/10.23919/ACC50511.2021.9483309
Qiao, Zhuoran; Ding, Feizhi et al. (2020) Multi-task learning for electronic structure to predict and explore molecular potential energy surfaces In: 34th Conference on Neural Information Processing Systems; arXiv; Series Advances in Neural Information Processing Systems; No. 33; In: 34th Conference on Neural Information Processing Systems (NeurIPS 2020), 6-12 December 2020, [Online Only] https://resolver.caltech.edu/CaltechAUTHORS:20201203-151028849
Nie, Weili; Yu, Zhiding et al. (2020) Bongard-LOGO: A New Benchmark for Human-Level Concept Learning and Reasoning In: Advances in Neural Information Processing Systems 33 pre-proceedings (NeurIPS 2020); arXiv; In: 34th Conference on Neural Information Processing Systems (NeurIPS 2020), 6-12 December 2020, [Online Only] https://resolver.caltech.edu/CaltechAUTHORS:20201109-074710530
Li, Yunzhu; Torralba, Antonio et al. (2020) Causal Discovery in Physical Systems from Videos In: Advances in Neural Information Processing Systems 33 pre-proceedings (NeurIPS 2020); arXiv; In: 34th Conference on Neural Information Processing Systems (NeurIPS 2020), 6-12 December 2020, [Online Only] https://resolver.caltech.edu/CaltechAUTHORS:20201109-123525639
Su, Jiahao; Byeon, Wonmin et al. (2020) Convolutional Tensor-Train LSTM for Spatio-temporal Learning In: Advances in Neural Information Processing Systems 33 pre-proceedings (NeurIPS 2020); arXiv; In: 34th Conference on Neural Information Processing Systems (NeurIPS 2020), 6-12 December 2020, [Online Only] https://resolver.caltech.edu/CaltechAUTHORS:20200402-134911700
Bernstein, Jeremy; Zhao, Jiawei et al. (2020) Learning compositional functions via multiplicative weight updates In: Advances in Neural Information Processing Systems 33 pre-proceedings (NeurIPS 2020); arXiv; In: 34th Conference on Neural Information Processing Systems (NeurIPS 2020), 6-12 December 2020, [Online Only] https://resolver.caltech.edu/CaltechAUTHORS:20201106-120208748
Lale, Sahin; Azizzadenesheli, Kamyar et al. (2020) Logarithmic Regret Bound in Partially Observable Linear Dynamical Systems In: Advances in neural information processing systems 33 pre-proceedings (NeurIPS 2020); In: 34th Conference on Neural Information Processing Systems (NeurIPS 2020), 6-12 December 2020, [Online Only] https://resolver.caltech.edu/CaltechAUTHORS:20221222-222544264
Li, Zongyi; Kovachki, Nikola et al. (2020) Multipole Graph Neural Operator for Parametric Partial Differential Equations In: Advances in Neural Information Processing Systems 33 pre-proceedings (NeurIPS 2020); arXiv; In: 34th Conference on Neural Information Processing Systems (NeurIPS 2020), 6-12 December 2020, [Online Only] https://resolver.caltech.edu/CaltechAUTHORS:20201106-120222366
Huang, Yujia; Gornet, James et al. (2020) Neural Networks with Recurrent Generative Feedback In: Advances in Neural Information Processing Systems 33 pre-proceedings (NeurIPS 2020); arXiv; In: 34th Conference on Neural Information Processing Systems (NeurIPS 2020), 6-12 December 2020, [Online Only] https://resolver.caltech.edu/CaltechAUTHORS:20201106-120201944
Anandkumar, Animashree (2020) Role of HPC in next-generation AI In: 2020 IEEE 27th International Conference on High Performance Computing, Data, and Analytics (HiPC); In: IEEE 27th International Conference on High Performance Computing, Data, and Analytics (HiPC), 16-19 December 2020, Pune, India https://doi.org/10.1109/hipc50609.2020.00010
Jiang, Chiyu Max; Esmaeilzadeh, Soheil et al. (2020) MESHFREEFLOWNET: A Physics-Constrained Deep Continuous Space-Time Super-Resolution Framework In: SC20: International Conference for High Performance Computing, Networking, Storage and Analysis; arXiv; In: SC20: International Conference for High Performance Computing, Networking, Storage and Analysis, 9-19 November 2020, Atlanta, GA https://doi.org/10.1109/SC41405.2020.00013
Baldini, Francesca; Anandkumar, Animashree et al. (2020) Learning Pose Estimation for UAV Autonomous Navigation and Landing Using Visual-Inertial Sensor Data In: 2020 American Control Conference (ACC); arXiv; In: 2020 American Control Conference (ACC), 1-3 July 2020, Denver, CO https://doi.org/10.23919/ACC45564.2020.9147400
Shi, Yang; Anandkumar, Animashree (2020) Higher-order Count Sketch: Dimensionality Reduction That Retains Efficient Tensor Operations In: 2020 Data Compression Conference (DCC); arXiv; In: 2020 Data Compression Conference (DCC), 24-27 March 2020, Snowbird, UT https://doi.org/10.1109/DCC47342.2020.00045
Schäfer, Florian; Anandkumar, Anima (2019) Competitive Gradient Descent In: 33rd Conference on Neural Information Processing Systems; 33rd Conference on Neural Information Processing Systems; In: 33rd Conference on Neural Information Processing Systems (NeurIPS), 8-14 December 2019, Vancouver, Canada https://resolver.caltech.edu/CaltechAUTHORS:20190905-154241002
Shi, Guanya; Shi, Xichen et al. (2019) Neural Lander: Stable Drone Landing Control using Learned Dynamics In: 2019 International Conference on Robotics and Automation (ICRA); arXiv; In: 2019 International Conference on Robotics and Automation (ICRA), 20-24 May 2019, Montreal, Canada https://doi.org/10.1109/ICRA.2019.8794351
Athiwaratkun, Ben; Wilson, Andrew Gordon et al. (2018) Probabilistic FastText for Multi-Sense Word Embeddings In: Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers); arXiv; In: 56th Annual Meeting of the Association for Computational Linguistics, 15-20 July 2018, Melbourne, Australia https://resolver.caltech.edu/CaltechAUTHORS:20190327-085800530
Shi, Yang; Furlanello, Tommaso et al. (2018) Question Type Guided Attention in Visual Question Answering In: Computer Vision – ECCV 2018; arXiv; Vol. IV; Series Lecture Notes in Computer Science; No. 11208; In: 15th European Conference on Computer Vision (ECCV 2018), 8-14 September 2018, Munich, Germany https://doi.org/10.1007/978-3-030-01225-0_10
Azizzadenesheli, Kamyar; Brunskill, Emma et al. (2018) Efficient Exploration Through Bayesian Deep Q-Networks In: 2018 Information Theory and Applications Workshop (ITA); In: 2018 Information Theory and Applications Workshop (ITA), 11-16 February 2018, San Diego, CA https://doi.org/10.1109/ita.2018.8503252
Kossaifi, Jean; Khanna, Aran et al. (2017) Tensor Contraction Layers for Parsimonious Deep Nets In: 2017 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW); In: 2017 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), 21-26 July 2017, Honolulu, HI https://doi.org/10.1109/CVPRW.2017.243
Wang, Yining; Anandkumar, Animashree (2016) Online and Differentially-Private Tensor Decomposition In: Neural Information Processing Systems 2016; arXiv; In: Advances in Neural Information Processing Systems 29 (NIPS 2016), 5-10 December 2016, Barcelona, Spain https://resolver.caltech.edu/CaltechAUTHORS:20190401-123322786
Shi, Yang; Niranjan, U. N. et al. (2016) Tensor Contractions with Extended BLAS Kernels on CPU and GPU In: 2016 IEEE 23rd International Conference on High Performance Computing; In: 2016 IEEE 23rd International Conference on High Performance Computing (HiPC), 19-22 December 2016, Hyderabad, India https://doi.org/10.1109/HiPC.2016.031
Wang, Yining; Tung, Hsiao-Yu et al. (2015) Fast and Guaranteed Tensor Decomposition via Sketching In: NIPS'15 Proceedings of the 28th International Conference on Neural Information Processing Systems; arXiv; Vol. 1; In: 28th International Conference on Neural Information Processing Systems (NIPS 15), 7-12 December 2015, Montreal, Canada https://resolver.caltech.edu/CaltechAUTHORS:20190401-123256793
Arabshahi, Forough; Huang, Furong et al. (2015) Are You Going to the Party: Depends, Who Else is Coming?: [Learning Hidden Group Dynamics via Conditional Latent Tree Models] In: 2015 IEEE International Conference on Data Mining; In: 2015 IEEE International Conference on Data Mining (ICDM), 14-17 November 2015, Atlantic City, NJ https://doi.org/10.1109/ICDM.2015.146
Anandkumar, Animashree; Ge, Rong et al. (2015) Tensor Decompositions for Learning Latent Variable Models (A Survey for ALT) In: Algorithmic Learning Theory; Series Lecture Notes in Computer Science; No. 9355; In: 26th International Conference on Algorithmic Learning Theory (ALT 2015), October 4-6, 2015, Banff, Canada https://doi.org/10.1007/978-3-319-24486-0_2
Sedghi, Hanie; Anandkumar, Anima et al. (2014) Multi-Step Stochastic ADMM in High Dimensions: Applications to Sparse Optimization and Matrix Decomposition In: Advances in neural information processing systems 27 : 28th Annual Conference on Neural Information Processing Systems 2014; In: 28th Annual Conference on Neural Information Processing Systems (NIPS 2014), 8-13 December 2014, Montréal, QB https://resolver.caltech.edu/CaltechAUTHORS:20221222-215036029
Netrapalli, Praneeth; Niranjan, U N et al. (2014) Provable Non-convex Robust PCA In: Advances in neural information processing systems 27 : 28th Annual Conference on Neural Information Processing Systems 2014; In: 28th Annual Conference on Neural Information Processing (NIPS 2014), 8-13 December 2014, Montréal, QB https://resolver.caltech.edu/CaltechAUTHORS:20221222-220846768
Anandkumar, Amod J. G.; Anandkumar, Animashree et al. (2013) Robust noncooperative rate-maximization game for MIMO Gaussian interference channels under bounded channel uncertainty In: 2013 IEEE International Conference on Acoustics, Speech and Signal Processing; In: 2013 IEEE International Conference on Acoustics, Speech and Signal Processing, 26-31 May 2013, Vancouver, BC https://doi.org/10.1109/ICASSP.2013.6638576
Huang, Furong; Anandkumar, Animashree (2013) FCD: Fast-concurrent-distributed load balancing under switching costs and imperfect observations In: 2013 Proceedings IEEE INFOCOM; In: 2013 Proceedings IEEE INFOCOM, 14-19 April 2013, Turin, Italy https://doi.org/10.1109/INFCOM.2013.6566989
Sattari, Pegah; Kurant, Maciej et al. (2013) Active learning of multiple source multiple destination topologies In: 47th Annual Conference on Information Sciences and Systems; In: 47th Annual Conference on Information Sciences and Systems (CISS), 20-22 March 2013, Baltimore, MD https://doi.org/10.1109/CISS.2013.6552253
Anandkumar, Anima; Foster, Dean P. et al. (2012) A Spectral Algorithm for Latent Dirichlet Allocation In: Advances in Neural Information Processing Systems 25: 26th Annual Conference on Neural Information Processing Systems 2012, NIPS 2012; In: 26th Annual Conference on Neural Information Processing Systems (NIPS 2012), 3-8 December 2012, Lake Tahoe, NV https://resolver.caltech.edu/CaltechAUTHORS:20221222-213700256
Anandkumar, Anima; Valluvan, Ragupathyraj (2012) Latent Graphical Model Selection: Efficient Methods for Locally Tree-like Graphs In: Advances in Neural Information Processing Systems 25: 26th Annual Conference on Neural Information Processing Systems 2012, NIPS 2012; In: 26th Annual Conference on Neural Information Processing Systems (NIPS 2012), 3-6 December 2012, Lake Tahoe, NV https://resolver.caltech.edu/CaltechAUTHORS:20221222-212818169
Anandkumar, Anima; Tan, Voncent Y. F. et al. (2011) High-Dimensional Graphical Model Selection: Tractable Graph Families and Necessary Conditions In: Advances in neural information processing systems 24 : 25th Annual Conference on Neural Information Processing Systems 2011, December 12-15, 2011, Granada, Spain; In: 25th Annual Conference on Neural Information Processing Systems (NIPS 2011), 12-15 December 2011, Granada, Spain https://resolver.caltech.edu/CaltechAUTHORS:20221222-193410312
Anandkumar, Animashree; Hsu, Daniel et al. (2011) Learning Mixtures of Tree Graphical Models In: Advances in neural information processing systems 24 : 25th Annual Conference on Neural Information Processing Systems 2011; In: 25th Annual Conference on Neural Information Processing Systems (NIPS 2011), 12-17 December 2011, Granada, Spain https://resolver.caltech.edu/CaltechAUTHORS:20221222-212034677
Anandkumar, Animashree; Chaudhuri, Kamalika et al. (2011) Spectral Methods for Learning Multivariate Latent Tree Structure In: Advances in neural information processing systems 24 : 25th Annual Conference on Neural Information Processing Systems 2011, December 12-15, 2011, Granada, Spain; In: 25th Annual Conference on Neural Information Processing Systems (NIPS 2011), 12-17 December 2011, Granada, Spain https://resolver.caltech.edu/CaltechAUTHORS:20221222-190922619
Khajehnejad, M. Amin; Yoo, Juhwan et al. (2011) Summary Based Structures with Improved Sublinear Recovery for Compressed Sensing In: 2011 IEEE International Symposium on Information Theory Proceedings; In: 2011 IEEE International Symposium on Information Theory (ISIT), Jul 31-Aug 05, 2011, St. Petersburg, Russia https://doi.org/10.1109/ISIT.2011.6033775
Balister, Paul; Bollobás, Béla et al. (2011) Energy-latency tradeoff for in-network function computation in random networks In: 2011 Proceedings IEEE INFOCOM; In: 2011 Proceedings IEEE INFOCOM, 10-15 April 2011, Shanghai, China https://doi.org/10.1109/INFCOM.2011.5934949
He, Ting; Anandkumar, Animashree et al. (2011) Index-based sampling policies for tracking dynamic networks under sampling constraints In: 2011 Proceedings IEEE INFOCOM; In: 2011 Proceedings IEEE INFOCOM, 10-15 April 2011, Shanghai, China https://doi.org/10.1109/INFCOM.2011.5934904
Anandkumar, Amod J. G.; Anandkumar, Animashree et al. (2010) Efficiency of rate-maximization game under bounded channel uncertainty In: 2010 Conference Record of the Forty Fourth Asilomar Conference on Signals, Systems and Computers; In: Forty Fourth Asilomar Conference on Signals, Systems and Computers (ASILOMAR), 2010, 7-10 November 2010, Pacific Grove, CA https://doi.org/10.1109/ACSSC.2010.5757605
Tan, Vincent Y. F.; Anandkumar, Animashree et al. (2010) Error exponents for composite hypothesis testing of Markov forest distributions In: 2010 IEEE International Symposium on Information Theory; In: 2010 IEEE International Symposium on Information Theory (ISIT 2010), 13-18 June 2010, Austin, TX https://doi.org/10.1109/ISIT.2010.5513399
Liu, Ying; Chandrasekaran, Venkat et al. (2010) Feedback Message Passing for Inference in Gaussian Graphical Models In: 2010 IEEE International Symposium on Information Theory Proceedings (ISIT) ; In: 2010 IEEE International Symposium on Information Theory (ISIT 2010), 13-18 June 2010, Austin, TX https://doi.org/10.1109/ISIT.2010.5513321
Anandkumar, Animashree; Yukich, Joseph et al. (2010) Limit laws for random spatial graphical models In: 2010 IEEE International Symposium on Information Theory; In: 2010 IEEE International Symposium on Information Theory (ISIT 2010), 13-18 June 2010, Austin, TX https://doi.org/10.1109/ISIT.2010.5513254
Anandkumar, Animashree; Michael, Nithin et al. (2010) Opportunistic Spectrum Access with Multiple Users: Learning under Competition In: 2010 Proceedings IEEE INFOCOM; In: 2010 IEEE INFOCOM, 15-19 March 2010, San Diego, CA https://doi.org/10.1109/INFCOM.2010.5462144
Anandkumar, Amod J. G.; Anandkumar, Animashree et al. (2010) Robust rate-maximization game under bounded channel uncertainty In: 2010 IEEE International Conference on Acoustics, Speech and Signal Processing; In: 2010 IEEE International Conference on Acoustics, Speech and Signal Processing, 14-19 March 2010, Dallas, TX https://doi.org/10.1109/ICASSP.2010.5496066
Tan, Vincent Y. F.; Anandkumar, Animashree et al. (2009) How do the structure and the parameters of Gaussian tree models affect structure learning? In: 47th Annual Allerton Conference on Communication, Control, and Computing; In: 47th Annual Allerton Conference on Communication, Control, and Computing, September 30 - October 2, 2009, Monticello, IL https://doi.org/10.1109/ALLERTON.2009.5394929
Tan, Vincent Y. F.; Anandkumar, Animashree et al. (2009) A large-deviation analysis for the maximum likelihood learning of tree structures In: 2009 IEEE International Symposium on Information Theory; In: 2009 IEEE International Symposium on Information Theory, June 28 - July 3, 2009, Seoul, Korea https://doi.org/10.1109/ISIT.2009.5206012
Anandkumar, Animashree; Tong, Lang et al. (2009) Detection error exponent for spatially dependent samples in random networks In: 2009 IEEE International Symposium on Information Theory; In: 2009 IEEE International Symposium on Information Theory, June 28 - July 3, 2009, Seoul, Korea https://doi.org/10.1109/ISIT.2009.5205358
Anandkumar, Animashree; Wang, Meng et al. (2009) Prize-Collecting Data Fusion for Cost-Performance Tradeoff in Distributed Inference In: 28th IEEE Conference on Computer Communications; In: 28th IEEE Conference on Computer Communications (INFOCOM 2009), 19-25 April 2009, Rio de Janeiro, Brazil https://doi.org/10.1109/INFCOM.2009.5062139
Ezovski, G. Matthew; Anandkumar, Animashree et al. (2008) Min-min times in peer-to-peer file sharing networks In: 46th Annual Allerton Conference on Communication, Control, and Computing; In: 46th Annual Allerton Conference on Communication, Control, and Computing, 23-26 September 2008, Urbana-Champaign, IL https://doi.org/10.1109/ALLERTON.2008.4797738
Anandkumar, Animashree; Bisdikian, Chatschik et al. (2008) Tracking in a spaghetti bowl: monitoring transactions using footprints In: Proceedings of the 2008 ACM SIGMETRICS international conference on measurement and modeling of computer systems; In: 2008 ACM SIGMETRICS international conference on measurement and modeling of computer systems (SIGMETRICS '08), 2-6 June 2008, Annapolis, MD https://doi.org/10.1145/1375457.1375473
Anandkumar, Animashree; Tong, Lang et al. (2008) Minimum Cost Data Aggregation with Localized Processing for Statistical Inference In: 27th IEEE Conference on Computer Communications; In: 27th IEEE Conference on Computer Communications (INFOCOM 2008), April 15-17, 2008, Phoenix, AZ https://doi.org/10.1109/INFOCOM.2008.129
Sengupta, Bikram; Banerjee, Nilanjan et al. (2008) Non-intrusive transaction monitoring using system logs In: 2008 IEEE Network Operations and Management Symposium; In: 2008 IEEE Network Operations and Management Symposium (NOMS 2008), 7-11 April 2008, Salvador, Bahia, Brazil https://doi.org/10.1109/NOMS.2008.4575237
Anandkumar, Animashree; Tong, Lang et al. (2007) Detection of Gauss-Markov Random Field on Nearest-Neighbor Graph In: 2007 IEEE International Conference on Acoustics, Speech and Signal Processing; In: 2007 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP '07), 15-20 April 2007, Honolulu, HI https://doi.org/10.1109/ICASSP.2007.366808
Anandkumar, Animashree; Tong, Lang et al. (2007) Energy Efficient Routing for Statistical Inference of Markov Random Fields In: 2007 41st annual conference on information sciences and systems : Baltimore, MD, 14-16 March, 2007.; In: 41stConference on Information Sciences and Systems, 14-16 March 2007, Baltimore, MD https://doi.org/10.1109/CISS.2007.4298386
Anandkumar, Animashree; Tong, Lang (2006) A Large Deviation Analysis of Detection Over Multi-Access Channels with Random Number of Sensors In: 2006 IEEE International Conference on Acoustics Speed and Signal Processing Proceedings; Vol. 4; In: 2006 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2006), 14-19 May 2006, Toulouse, France https://doi.org/10.1109/ICASSP.2006.1661164
Anandkumar, Animashree; Tong, Lang (2006) Distributed Statistical Inference using Type Based Random Access over Multi-access Fading Channels In: 2006 40th Annual Conference on Information Sciences and Systems; In: 2006 40th Annual Conference on Information Sciences and Systems, 22-24 March 2006, Princeton, NJ https://doi.org/10.1109/CISS.2006.286427