Papers
Cautious Adaptation For Reinforcement Learning in Safety-Critical Settings
Jesse Zhang, Brian Cheung, Chelsea Finn et al.
Certified Data Removal from Machine Learning Models
Chuan Guo, Tom Goldstein, Awni Hannun et al.
Certified Robustness to Label-Flipping Attacks via Randomized Smoothing
Elan Rosenfeld, Ezra Winston, Pradeep Ravikumar et al.
Channel Equilibrium Networks for Learning Deep Representation
Wenqi Shao, Shitao Tang, Xingang Pan et al.
Characterizing Distribution Equivalence and Structure Learning for Cyclic and Acyclic Directed Graphs
Amiremad Ghassami, Alan Yang, Negar Kiyavash et al.
Choice Set Optimization Under Discrete Choice Models of Group Decisions
Kiran Tomlinson, Austin Benson
Circuit-Based Intrinsic Methods to Detect Overfitting
Satrajit Chatterjee, Alan Mishchenko
Class-Weighted Classification: Trade-offs and Robust Approaches
Ziyu Xu, Chen Dan, Justin Khim et al.
Clinician-in-the-Loop Decision Making: Reinforcement Learning with Near-Optimal Set-Valued Policies
Shengpu Tang, Aditya Modi, Michael Sjoding et al.
Closed Loop Neural-Symbolic Learning via Integrating Neural Perception, Grammar Parsing, and Symbolic Reasoning
Qing Li, Siyuan Huang, Yining Hong et al.
Closing the convergence gap of SGD without replacement
Shashank Rajput, Anant Gupta, Dimitris Papailiopoulos
CLUB: A Contrastive Log-ratio Upper Bound of Mutual Information
Pengyu Cheng, Weituo Hao, Shuyang Dai et al.
Collaborative Machine Learning with Incentive-Aware Model Rewards
Rachael Hwee Ling Sim, Yehong Zhang, Mun Choon Chan et al.
Collapsed Amortized Variational Inference for Switching Nonlinear Dynamical Systems
Zhe Dong, Bryan Seybold, Kevin Murphy et al.
Combinatorial Pure Exploration for Dueling Bandit
Wei Chen, Yihan Du, Longbo Huang et al.
Combining Differentiable PDE Solvers and Graph Neural Networks for Fluid Flow Prediction
Filipe De Avila Belbute-Peres, Thomas Economon, Zico Kolter
CoMic: Complementary Task Learning & Mimicry for Reusable Skills
Leonard Hasenclever, Fabio Pardo, Raia Hadsell et al.
Communication-Efficient Distributed PCA by Riemannian Optimization
Long-Kai Huang, Sinno Pan
Communication-Efficient Distributed Stochastic AUC Maximization with Deep Neural Networks
Zhishuai Guo, Mingrui Liu, Zhuoning Yuan et al.
Complexity of Finding Stationary Points of Nonconvex Nonsmooth Functions
Jingzhao Zhang, Hongzhou Lin, Stefanie Jegelka et al.
Composable Sketches for Functions of Frequencies: Beyond the Worst Case
Edith Cohen, Ofir Geri, Rasmus Pagh
Compressive sensing with un-trained neural networks: Gradient descent finds a smooth approximation
Reinhard Heckel, Mahdi Soltanolkotabi
Computational and Statistical Tradeoffs in Inferring Combinatorial Structures of Ising Model
Ying Jin, Zhaoran Wang, Junwei Lu
Concentration bounds for CVaR estimation: The cases of light-tailed and heavy-tailed distributions
Prashanth L.A., Krishna Jagannathan, Ravi Kolla
Concept Bottleneck Models
Pang Wei Koh, Thao Nguyen, Yew Siang Tang et al.