Papers
Estimating Model Uncertainty of Neural Networks in Sparse Information Form
Jongseok Lee, Matthias Humt, Jianxiang Feng et al.
Estimating Q(s,s’) with Deep Deterministic Dynamics Gradients
Ashley Edwards, Himanshu Sahni, Rosanne Liu et al.
Estimating the Error of Randomized Newton Methods: A Bootstrap Approach
Jessie X.T. Chen, Miles Lopes
Estimating the Number and Effect Sizes of Non-null Hypotheses
Jennifer Brennan, Ramya Korlakai Vinayak, Kevin Jamieson
Estimation of Bounds on Potential Outcomes For Decision Making
Maggie Makar, Fredrik Johansson, John Guttag et al.
Evaluating Lossy Compression Rates of Deep Generative Models
Sicong Huang, Alireza Makhzani, Yanshuai Cao et al.
Evaluating Machine Accuracy on ImageNet
Vaishaal Shankar, Rebecca Roelofs, Horia Mania et al.
Evaluating the Performance of Reinforcement Learning Algorithms
Scott Jordan, Yash Chandak, Daniel Cohen et al.
Evolutionary Reinforcement Learning for Sample-Efficient Multiagent Coordination
Somdeb Majumdar, Shauharda Khadka, Santiago Miret et al.
Evolutionary Topology Search for Tensor Network Decomposition
Chao Li, Zhun Sun
Explainable and Discourse Topic-aware Neural Language Understanding
Yatin Chaudhary, Hinrich Schuetze, Pankaj Gupta
Explainable k-Means and k-Medians Clustering
Michal Moshkovitz, Sanjoy Dasgupta, Cyrus Rashtchian et al.
Explaining Groups of Points in Low-Dimensional Representations
Gregory Plumb, Jonathan Terhorst, Sriram Sankararaman et al.
Explicit Gradient Learning for Black-Box Optimization
Elad Sarafian, Mor Sinay, Yoram Louzoun et al.
Exploration Through Reward Biasing: Reward-Biased Maximum Likelihood Estimation for Stochastic Multi-Armed Bandits
Xi Liu, Ping-Chun Hsieh, Yu Heng Hung et al.
Explore, Discover and Learn: Unsupervised Discovery of State-Covering Skills
Victor Campos, Alexander Trott, Caiming Xiong et al.
Extra-gradient with player sampling for faster convergence in n-player games
Samy Jelassi, Carles Domingo-Enrich, Damien Scieur et al.
Extrapolation for Large-batch Training in Deep Learning
Tao Lin, Lingjing Kong, Sebastian Stich et al.
Extreme Multi-label Classification from Aggregated Labels
Yanyao Shen, Hsiang-Fu Yu, Sujay Sanghavi et al.
FACT: A Diagnostic for Group Fairness Trade-offs
Joon Sik Kim, Jiahao Chen, Ameet Talwalkar
Fair Generative Modeling via Weak Supervision
Kristy Choi, Aditya Grover, Trisha Singh et al.
Fair k-Centers via Maximum Matching
Matthew Jones, Huy Nguyen, Thy Nguyen
Fair Learning with Private Demographic Data
Hussein Mozannar, Mesrob Ohannessian, Nathan Srebro
Fairwashing explanations with off-manifold detergent
Christopher Anders, Plamen Pasliev, Ann-Kathrin Dombrowski et al.