Papers
Can Autonomous Vehicles Identify, Recover From, and Adapt to Distribution Shifts?
Angelos Filos, Panagiotis Tigkas, Rowan Mcallister et al.
Can Increasing Input Dimensionality Improve Deep Reinforcement Learning?
Kei Ota, Tomoaki Oiki, Devesh Jha et al.
Can Stochastic Zeroth-Order Frank-Wolfe Method Converge Faster for Non-Convex Problems?
Hongchang Gao, Heng Huang
Causal Effect Estimation and Optimal Dose Suggestions in Mobile Health
Liangyu Zhu, Wenbin Lu, Rui Song
Causal Effect Identifiability under Partial-Observability
Sanghack Lee, Elias Bareinboim
Causal Inference using Gaussian Processes with Structured Latent Confounders
Sam Witty, Kenta Takatsu, David Jensen et al.
Causal Modeling for Fairness In Dynamical Systems
Elliot Creager, David Madras, Toniann Pitassi et al.
Causal Strategic Linear Regression
Yonadav Shavit, Benjamin Edelman, Brian Axelrod
Causal Structure Discovery from Distributions Arising from Mixtures of DAGs
Basil Saeed, Snigdha Panigrahi, Caroline Uhler
CAUSE: Learning Granger Causality from Event Sequences using Attribution Methods
Wei Zhang, Thomas Panum, Somesh Jha et al.
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.