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Past talks
Fall 2023 Talks
| Oct 13 | Alireza Fallah (MSRI and UC Berkeley) | Privacy Mechanisms for Data MarketsI | details |
| Oct 20 | Surbhi Goel (U Penn) | Beyond Worst-case Sequential Prediction: Adversarial Robustness via Abstention | details |
| 2-3pm PT, Oct 26 | Chiwei Yan (UC Berkeley IEOR) | Incentive-aware Dynamic Matching Problems | details |
| Nov 3 | Jingyan Wang (Georgia Tech) | Modeling and Correcting Bias in Sequential Evaluation | details |
| Nov 10 | Aryan Mokhtari (UT Austin) | Online Learning Guided Quasi-Newton Methods: Improved Global Non-asymptotic Guarantees | details |
| Nov 17 | Gaurav Mahajan (Yale) | | details |
| Nov 24 | Thanksgiving break | - | - |
| Dec 1 | Jason Altschuler (University of Pennsylvania) | | details |
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Spring 2023 Talks
| March 1 | Ananya Kumar (Stanford) | Foundation Models for Robustness to Distribution Shifts | details |
| March 15 | Ayush Sekhari (MIT) | On the Complexity of Adversarial Decision Making | details |
| March 22 | Venugopal Veeravalli (UIUC) | Quickest Change Detection for Monitoring Pandemics | details |
| March 29 | Spring break | - | - |
| April 5 | Max Simchowitz (MIT) | Randomized Smoothing, Online Learning, and Planning Through Contact. | details |
| April 12 | Gautam Goel (Simons Institute) | Competitive Control | details |
| 10-11am PT, April 19 | Yair Carmon (Tel Aviv University) | Stochastic gradient descent without learning rate tuning | details |
| 10-11am PT, April 26 | Ramon Van Handel (Princeton) | A new approach to nonasymptotic random matrix theory | details |
| May 3 | | | details |
| May 10 | Ari Morcos (FAIR) | | details |
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Fall 2022 Talks
| Friday, August 26, 3-4 PM | Weijie Su (U Penn) | When Will You Become the Best Reviewer of Your Own Papers? A Mechanism-Design-Based Approach to Statistical Estimation | details |
| August 29 | Haipeng Luo (USC) | Near-Optimal No-Regret Learning for General Convex Games — The Role of Positive Regret | details |
| Oct 10 | Yuxin Chen (U Penn) | Towards Optimal Sample Complexities in Offline Reinforcement Learning and Markov Games | details |
| Oct 17 | Wen Sun (Cornell) | Hybrid RL: Using both offline and online data can make RL efficient | details |
| Oct 24 | Chen-Yu Wei (Simons) | Optimal Dynamic Regret for Bandits without Prior Knowledge | details |
| Oct 31 | Wenlong Mou (UC Berkeley) | Rethinking semi-parametric efficiency for off-policy estimation: a non-asymptotic perspective | details |
| Tuesday, Nov 1, 2-3 PM | Kevin Jamieson (University of Washington) | Towards Instance-Optimal Algorithms for Reinforcement Learning | details |
| Nov 14 | Raaz Dwivedi (Harvard and MIT) | Two vignettes on efficient procedures for personalized decision making | details |
| Nov 28 | Gautam Kamath and Mahbod Majid (University of Waterloo) | Efficient Mean Estimation with Pure Differential Privacy via a Sum-Of-Squares Exponential Mechanism | details |
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Spring 2022 Talks
Talk recordings from Spring 2022 are available here.
| Jan 26 | Qian Yu (Princeton) | Coding Theory for Large-scale Distributed Computing | details |
| Feb 2 | Yury Polyanskiy (MIT) | Rates of convergence of Gaussian smoothed empirical measures in Wasserstein and KL distances | details |
| Feb 9 | Chenguang Zhu (MSR) | How We Achieved Human Parity in CommonsenseQA – Fusing Knowledge into Language Models | details |
| Feb 18, 9:30-10:30 AM PT | Kangwook Lee (Wisconsin-Madison) | Improving Fairness via Federated Learning | details |
| Mar 2 | Ashwin Pananjady (Georgia Tech) | Sharp convergence guarantees for iterative algorithms in random optimization problems | details |
| Mar 9 | Sai Praneeth Karimireddy (UC Berkeley) | Byzantine robust collaborative learning | details |
| Mar 16 | speaker | title | details |
| Mar 30 | Yuansi Chen (Duke) | Localization schemes: A framework for proving mixing bounds for Markov chains | details |
| Apr 6 | Yuanzhi Li (CMU) | Deep learning when the data set has multiple features | details |
| Apr 13 | Vidya Muthukumar (Georgia Tech) | Classification versus regression in overparameterized regimes: Does the loss function matter? | details |
| Apr 27 | Dylan Foster (Microsoft Research) | The Statistical Complexity of Interactive Decision Making | details |
| May 4 | Quanquan Gu (UCLA) | Stochastic Gradient Descent: Benign Overfitting and Implicit Regularization | details |
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Fall 2021 Talks
Talk recordings from Fall 2021 are available here.
| Sep 10 | Simon Du (University of Washington) | Horizon-Free Reinforcement Learning | details |
| Sep 17 | Hessam Mahdavifar (University of Michigan) | Machine Learning-Aided Channel Coding: Opportunities and Challenges | details |
| Sep 24 | Jingbo Liu (UIUC) | A few interactions improve distributed nonparametric estimation | details |
| Oct 15 | Xiaowu Dai (UC Berkeley) | Statistical Learning and Market Design | details |
| Oct 22 | Dheeraj Nagaraj (MIT) | Reverse Experience Replay: A Streaming Method to Learn with Dependent Data | details |
| Oct 29 | Angela Zhou (UC Berkeley) | Robust Policy Learning and Evaluation under Unobserved Confounding | details |
| Nov 12 | Suvrit Sra (MIT) | Some surprising gaps between optimization theory and ML practice | details |
| Nov 19 | Junchi Li (UC Berkeley) | Some Recent Progress in Nonconvex and Statistical Optimization | details |
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Spring 2021 Talks
Talk recordings from Spring 2021 are available here.
| Jan 29 | Lin Chen (UC Berkeley) | Deep Neural Tangent Kernel and Laplace Kernel Have the Same RKHS | details |
| Feb 12 | Michał Dereziński (UC Berkeley) | Bridging algorithmic and statistical randomness in machine learning | details |
| Feb 19 | Lin F. Yang (UCLA) | Efficient methods for reinforcement learning with general function approximation | details |
| Feb 26 | Song Mei (UC Berkeley) | The efficiency of kernel methods on structured datasets | details |
| Mar 5 | Chi Jin (Princeton) | Bellman Eluder Dimension: New Rich Classes of RL Problems, and Sample-Efficient Algorithms | details |
| Mar 12 | R Srikant (UIUC) | Sample Complexity and Overparameterization Bounds for Neural Temporal Difference Learning | details |
| Mar 19 | Alex Dimakis (UT Austin) | Deep Generative models and Inverse Problems | details |
| Mar 26 | Spring break | | |
| Apr 2 | Miaoyan Wang (UW Madison) | Beyond the Signs: Nonparametric Tensor Completion via Sign Series | details |
| Apr 9 | Nhat Ho (UT Austin) | Instability, Computational Efficiency and Statistical Accuracy | details |
| Apr 16 | Aarti Singh (CMU) | Learning from preferences and labels | details |
| Apr 23 | Salman Avastimehr (USC) | Trustworthy and Scalable Federated Learning | details |
| Apr 30 | Nihar Shah (CMU) | Two F-words in Peer Review (Fraud and Feedback) | details |
| May 7 | Jiaming Xu (Duke) | The planted matching problem: Sharp threshold and infinite-order phase transition | details |
| May 14 | Alekh Agarwal (Microsoft Research) | Towards a Theory of Representation Learning for Reinforcement Learning | details |
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Fall 2020 Talks
Talk recordings from Fall 2020 are available here.
| Sep 11 | Sam Hopkins (UC Berkeley) | Recent Advances in Algorithmic Heavy-Tailed Statistics | details |
| Sep 18 | Yuanzhi Li (CMU) | Backward Feature Correction: How can Deep Learning perform Deep Learning? | details |
| Sep 25 | Steve Hanneke (TTIC) | Multi-task Learning: Optimal Rates and a No-Free-Lunch Theorem | details |
| Oct 2 | Haipeng Luo (USC) | From bandits to MDPs: optimally and adaptively learning episodic MDPs with adversarial losses | details |
| Oct 9 | Wen Sun (Cornell) | Exploration and Robustness in Policy Gradient Learning | details |
| Oct 16 | Dimitris Papailiopoulos (Wisconsin-Madison) | Learning is Pruning | details |
| Oct 19 | Jerry Li (Microsoft) | Faster and Simpler Algorithms for List Learning | details |
| Oct 23 | Pulkit Grover (CMU) | Measures of Information Flows in Natural and Artificial Computational Systems | details |
| Oct 30 | Sharon Li (Wisconsin-Madison) | Reliable Open-World Learning Against Out-of-distribution Data | details |
| Nov 6 | Cong Ma (UC Berkeley) | Bridging convex and nonconvex optimization in noisy matrix completion: Stability and uncertainty quantification | details |
| Nov 13 | Kangwook Lee (UW Madison) | Make-or-break issues in fair classification | details |
| Nov 20 | Zhizhen Zhao (UIUC) | Exploiting Group and Geometric Structures for Massive Data Analysis | details |
| Dec 4 | Aaron Wagner (Cornell) | What Hockey Teams and Foraging Animals Can Teach Us About Feedback Communication | details |
| Dec 11 | Anru Zhang (Wisconsin-Madison) | Importance Sketching for Fast Low-rank Matrix/Tensor Learning: Algorithm and High-order Convergence | details |
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Spring 2020 Talks
| Feb 11 | Siva Theja Maguluri (Georgia Tech) | Finite Sample Convergence Bounds of Off-Policy Reinforcement Learning Algorithms | details |
| Feb 12 | Krishnakumar Balasubramanian (UC Davis) | Normal Approximations for Stochastic Iterative Estimators (and Martingales) | details |
| Feb 19 | Alon Kipnis (Stanford) | Two-sample Problem for High-Dimensional Multinomials and Testing Authorship | details |
| Feb 26 | David Tse (Stanford) | Blockchains, branching random walks and the number e | details |
| Feb 28 | Aly El Gamal (Purdue) | Information Theory and Deep Learning for Future Wireless Networks | details |
| Mar 4 | David Hong (UPenn) | Understanding Parallel Analysis Methods for Rank Selection in PCA | details |
| | Rest of the talks were cancelled due to COVID-19 outbreak. | |
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Fall 2019
| Aug 28 | Ramya Vinayak (UW Seattle) | Learning from Sparse Data | details |
| Sep 18 | Arya Mazumdar (UMass) | Sample complexity of mixture of sparse linear regressions | details |
| Sep 25 | Feng Ruan (UC Berkeley) | Searching for Interactions in Linear Time | details |
| Oct 2 | Amir Gholami (UC Berkeley) | Systematic Quantization of Neural Networks Through Second-Order Information | details |
| Oct 9 | Nhat Ho (UC Berkeley) | Statistical and computational perspective of mixture and hierarchical models | details |
| Oct 18 | Jiaming Xu (Duke) | Spectral graph matching and regularized quadratic relaxations | details |
| Oct 30 | Cheuk Ting Li (UC Berkeley) | One-shot Information Theory via Poisson Processes | details |
| Nov 6 | Yuejie Chi (CMU) | Distributed Stochastic Optimization with Variance Reduction and Gradient Tracking | details |
| Nov 13 | Guy Bresler (MIT) | Towards an Average-case Complexity of High-dimensional Statistics | details |
| Nov 20 | Victoria Kostina (Caltech) | Towards a Theory of Information for Dynamical Systems | details |
| Dec 4 | Animesh Kumar (IIT Bombay) | On sampling and inference of spatial fields from samples taken by a location-unaware mobile sensor | details |
| Dec 6 | Jingbo Liu (MIT) | Gaussian limits in two inference problems | details |
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Spring 2019
| Feb 4 | Clement Canonne (Stanford) | Statistical Inference Under Local Information Constraints | details |
| Feb 25 | Gautam Kamath (Simons) | Privately Learning High-Dimensional Distributions | details |
| Mar 4 | Yuandong Tian (Facebook AI) | Reproducing AlphaZero: what we learn | details |
| Mar 11 | Lalitha Sankar (Arizona State) | Information-theoretic Privacy: Leakage, robustness, and mechanism design | details |
| Mar 15 | Deniz Gunduz (Imperial College London) | Learn to Communicate - Communicate to Learn | details |
| Mar 20 | Elisa Celis (EPFL) | Fairness in Machine Learning for Online Social Systems | details |
| Apr 1 | Aaditya Ramdas (CMU) | On the bias, risk and consistency of sample means in multi-armed bandits | details |
| Apr 8 | Piyush Srivastava (TIFR) | Structure recovery in graphical models | details |
| Apr 15 | Steven Wu (U. Minnesota) | How to Use Heuristics for Differential Privacy | details |
| Apr 24 | Farzan Farnia (Stanford) | A Convex Duality Framework for GANs | details |
| Apr 29 | Katrina Ligett (HUJI) | A necessary and sufficient stability notion for adaptive generalization | details |
| May 6 | Anand Sarwate (Rutgers) | Between Shannon and Hamming: how bad can the channel be? | details |
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Fall 2018
| Aug 27 | Jingbo Liu (MIT) | Reverse hypercontractivity beats measure concentration for information theoretic converses | details |
| Sep 5 | Lav Varshney (UIUC) | Information-Theoretic Approaches to Clustering and Interpretable Concept Learning | details |
| Sep 10 | Maryam Fazel (UW Seattle) | Online Competitive Algorithms for Resource Allocation | details |
| Oct 2 | Yan Shuo Tan | Efficient algorithms for phase retrieval in high dimension | details |
| Oct 10 | Uzi Pereg (Technion) | Arbitrarily Varying Broadcast and Relay Channels | details |
| Oct 15 | Ruoyu Sun (UIUC) | Understanding Landscape of Neural Networks for Binary Classification | details |
| Oct 26 | Nihar Shah (CMU) | Battling Demons in Peer Review | details |
| Oct 29 | Deanna Needell (UCLA) | Iterative projective approaches for inconsistent and massively corrupted systems | details |
| Nov 1 | Yingbin Liang (Ohio State) | SGD Converges to Global Minimum in Deep Learning via Star-Convex Path | details |
| Nov 6 | Laura Balzano (Michigan) | Non-linear matrix completion | details |
| Nov 14 | Henk Wymeersch (Chalmers) | 5G Positioning for Connected Vehicles | details |
| Nov 26 | Mary Wootters (Stanford) | Two Stories about Group Testing | details |
| Dec 3 | Sreeram Kannan (UW Seattle) | Deconstructing the Blockchain to approach physical limits | details |
| Dec 10 | Yuval Cassuto (Technion) | Beyond Repair: Codes with Random Access | details |
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Spring 2018
| Jan 26 | Sivan Toledo (Tel-Aviv) | The ATLAS Reverse-GPS System: High-Throughput Wildlife Tracking | details |
| Feb 7 | Raymond Yeung (CUHK) | Shannon's Information Measures and Markov Structures | details |
| Feb 22 | Yuantao Gu (Tsinghua) | RIP of Random Projection for Low-Dimensional Subspaces | details |
| Mar 9 | John Wright (Columbia) | Nonconvex Sparse Deconvolution: Geometry and Efficient Methods | details |
| Mar 12 | Reinhard Heckel (Rice) | Robust Storage of Information in DNA Molecules | details |
| Mar 19 | R. Srikant (UIUC) | Queues, Balls and Bins, and Association | details |
| Mar 23 | Angie Wang (Berkeley) | An Agile Approach to FFTs and Hardware DSP Generation | details |
| Apr 2 | Balaji Prabhakar (Stanford) | Self-Programming Networks: Architecture and Algorithms | details |
| Apr 9 | Bruce Hajek (UIUC) | Gene regulatory network reconstruction from high throughput sequencing data | details |
| Apr 12 | Jun Chen (McMaster) | From Gaussian Multiterminal Source Coding to DistributedKarhunen–Loève Transform | details |
| Apr 16 | Sid Banerjee (Cornell) | Allocating Resources, in the Future | details |
| Apr 23 | Inderjit Dhillon (A9) | Stabilizing Gradients for Deep Neural Networks | details |
| Apr 30 | Leo Miolane (INRIA) | Phase transitions in generalized linear models | details |
| May 4 | Fanny Yang (Berkeley) | Computational guarantees for statistical learning algorithms | details |
| May 7 | Eva Tardos (Cornell) | Learning with Low Approximate Regret with Partial Feedback | details |
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Fall 2017
| Sep 25 | Stephen Wright (UW Madison) | Algorithmic Tools for Smooth Nonconvex Optimization | details |
| Oct 2 | Stefanie Jegelka (MIT) | Submodularity and Optimal Transport in ML | details |
| Oct 4 | Gerald Friedland (Berkeley) | Capacity Scaling of Neural Networks | details |
| Oct 9 | Zeyuan Allen-Zhu (Microsoft Research) | Optimal Experimental Design via Regret Minimization | details |
| Oct 16 | Yin Tat Lee (U. Washington) | Kannan-Lovasz-Simonovitz (KLS) conjecture | details |
| Oct 23 | Sebastien Bubeck (Microsoft Research) | Sparsity, variance, and curvature in multi-armed bandits | details |
| Oct 30 | Ludwig Schmidt (MIT) | Efficiently Optimizing over (Non-Convex) Cones Using Approximate Projections | details |
| Nov 6 | Jiantao Jiao (Stanford) | Modern Estimation of Information Theoretic Functionals | details |
| Nov 8 | Mina Karzand (MIT) | Regret bounds for a latent variable recommendation systems model | details |
| Nov 13 | Lieven Vandenberghe (UCLA) | Primal-dual first-order methods for convex optimization | details |
| Nov 20 | Chi Jin (Berkeley) | How to Escape Saddle Points Efficiently | details |
| Nov 22 | Shusen Wang (Berkeley) | Communication-Efficient Distributed Optimization via a 2nd-Order Method | details |
| Nov 27 | Philipp Walk (Caltech) | Blind Deconvolution Methods for Short Message Communications | details |
| Dec 11 | Marco Mondelli (Stanford) | Fundamental Limits of Weak Recovery with Applications to Phase Retrieval | details |
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Spring 2017
| Jan 30 | Vincent Poor (Princeton) | Network Analysis Problems Motivated by the Smart Grid | details |
| Feb 6 | Victoria Kostina (Caltech) | Information-theoretic tradeoffs in control | details |
| Feb 8 | Ziv Goldfeld (Ben-Gurion) | Semantic security versus active adversaries | details |
| Feb 13 | Reinhard Heckel (Berkeley) | Active Ranking from Pairwise Comparisons | details |
| Feb 21 | Ilan Shomorony (Berkeley) | DNA Sequencing: From Information Limits to Assembly Software | details |
| Feb 27 | Haim Permuter (Ben-Gurion) | Causality and directed information | details |
| Mar 6 | Lele Wang (Stanford) | Graph information ratio | details |
| Mar 13 | Matus Telgarsky (UIUC) | Logistic regression convergence rates | details |
| Mar 17 | Yuval Cassuto (Technion) | Coded Network Switches | details |
| Mar 20 | Aditya Mahajan (McGill) | Fundamental limits of remote estimation | details |
| Mar 30 | Rob Nowak (UW Madison) | Ordinal Embedding | details |
| Apr 3 | Amin Karbasi (Yale) | Cracking Big Data with Small Data | details |
| Apr 6 | Anthony Quinn (Dublin/Berkeley) | Fully Probabilistic Design for External Stochastic Knowledge Processing | details |
| Apr 10 | Aaditya Ramdas (Berkeley) | Decentralized decision making on networks with false discovery rate control | details |
| Apr 17 | Ayfer Ozgur (Stanford) | Cover’s Open Problem: “Capacity of the Relay Channel” | details |
| Apr 20 | Carlee Joe-Wong (CMU) | Letting Go of Network Neutrality | details |
| Apr 24 | Suvrit Sra (MIT) | Geometric optimization: convex and nonconvex | details |
| May 8 | Nihar Shah (Berkeley) | Learning from People | details |
| May 26 | Shlomo Shamai (Technion) | Information-Estimation Relations in Gaussian Networks | details |
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Fall 2016
| Aug 22 | Shashanka Ubaru (UMN) | Codes for low-rank approximation and group testing | details |
| Aug 29 | Carl Simon-Gabriel (Tubingen) | Kernel Mean Embeddings: A Quick Guided Tour | details |
| Aug 31 | Rashmi KV (Berkeley) | Erasure Coding for Big-data Systems | details |
| Sep 6 | Michael Gastpar (EPFL) | Towards an Algebraic Network Information Theory | details |
| Sep 16 | Animesh Kumar (IIT-B) | Bandlimited Estimation by Location-Unaware Sensors | details |
| Sep 19 | Ilan Ben Bassat (Tel Aviv) | Hashing and Sampling for Genome Assembly | details |
| Oct 10 | Ramya Srinivasan (Intel) | Beyond GPS: high accuracy smartphone technologies | details |
| Oct 17 | Ahmed El Alaoui (Berkeley) | Decoding from Random Histogram Queries | details |
| Oct 24 | Somayeh Sojoudi (Berkeley) | Data-driven sparse network estimation | details |
| Oct 31 | Lifeng Lai (Davis) | Distributed Inference with Compressed Data | details |
| Nov 4 | Yue Lu (Harvard) | Phase Transitions in Stochastic Optimization | details |
| Nov 14 | Jingge Zhu (Berkeley) | Structured Codes in Multi-user Communication | details |
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Spring 2016
| Jan 25 | James Zou (MSR/ MIT) | details |
| Feb 22 | Xiugang Wu (Stanford) | details |
| Feb 29 | Idoia Ochoa (Stanford) | details |
| Mar 1 | Julien Mairal (INRIA) | details |
| Mar 16 | Marco Cuturi (Kyoto) | details |
| Apr 11 | Aditya Ramamoorthy (Iowa state) | details |
| Apr 18 | Dimitris Papailiopoulos (Berkeley) | details
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Older talks
Visit the (no longer maintained) NCD seminar webpage.
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