Papers
11,015 papers found
Estimating Gradients for Discrete Random Variables by Sampling without Replacement
Wouter Kool, Herke van Hoof, Max Welling
Evaluating The Search Phase of Neural Architecture Search
Kaicheng Yu, Christian Sciuto, Martin Jaggi et al.
Evolutionary Population Curriculum for Scaling Multi-Agent Reinforcement Learning
Qian Long*, Zihan Zhou*, Abhinav Gupta et al.
Expected Information Maximization: Using the I-Projection for Mixture Density Estimation
Philipp Becker, Oleg Arenz, Gerhard Neumann
Explain Your Move: Understanding Agent Actions Using Specific and Relevant Feature Attribution
Nikaash Puri, Sukriti Verma, Piyush Gupta et al.
Explanation by Progressive Exaggeration
Sumedha Singla, Brian Pollack, Junxiang Chen et al.
Exploration in Reinforcement Learning with Deep Covering Options
Yuu Jinnai, Jee Won Park, Marlos C. Machado et al.
Exploratory Not Explanatory: Counterfactual Analysis of Saliency Maps for Deep Reinforcement Learning
Akanksha Atrey, Kaleigh Clary, David Jensen
Exploring Model-based Planning with Policy Networks
Tingwu Wang, Jimmy Ba
Extreme Classification via Adversarial Softmax Approximation
Robert Bamler, Stephan Mandt
Extreme Tensoring for Low-Memory Preconditioning
Xinyi Chen, Naman Agarwal, Elad Hazan et al.
Fair Resource Allocation in Federated Learning
Tian Li, Maziar Sanjabi, Ahmad Beirami et al.
Fantastic Generalization Measures and Where to Find Them
Yiding Jiang*, Behnam Neyshabur*, Hossein Mobahi et al.
FasterSeg: Searching for Faster Real-time Semantic Segmentation
Wuyang Chen, Xinyu Gong, Xianming Liu et al.
Fast is better than free: Revisiting adversarial training
Eric Wong, Leslie Rice, J. Zico Kolter
Fast Neural Network Adaptation via Parameter Remapping and Architecture Search
Jiemin Fang*, Yuzhu Sun*, Kangjian Peng* et al.
Fast Task Inference with Variational Intrinsic Successor Features
Steven Hansen, Will Dabney, Andre Barreto et al.
Feature Interaction Interpretability: A Case for Explaining Ad-Recommendation Systems via Neural Interaction Detection
Michael Tsang, Dehua Cheng, Hanpeng Liu et al.
Federated Adversarial Domain Adaptation
Xingchao Peng, Zijun Huang, Yizhe Zhu et al.
Federated Learning with Matched Averaging
Hongyi Wang, Mikhail Yurochkin, Yuekai Sun et al.
FEW-SHOT LEARNING ON GRAPHS VIA SUPER-CLASSES BASED ON GRAPH SPECTRAL MEASURES
Jatin Chauhan, Deepak Nathani, Manohar Kaul
Few-shot Text Classification with Distributional Signatures
Yujia Bao, Menghua Wu, Shiyu Chang et al.
Finding and Visualizing Weaknesses of Deep Reinforcement Learning Agents
Christian Rupprecht, Cyril Ibrahim, Christopher J. Pal
Finite Depth and Width Corrections to the Neural Tangent Kernel
Boris Hanin, Mihai Nica
Fooling Detection Alone is Not Enough: Adversarial Attack against Multiple Object Tracking
Yunhan Jia, Yantao Lu, Junjie Shen et al.