Papers
DNA: Domain Generalization with Diversified Neural Averaging
Xu Chu, Yujie Jin, Wenwu Zhu et al.
DNNR: Differential Nearest Neighbors Regression
Youssef Nader, Leon Sixt, Tim Landgraf
DNS: Determinantal Point Process Based Neural Network Sampler for Ensemble Reinforcement Learning
Hassam Sheikh, Kizza Frisbee, Mariano Phielipp
Do Differentiable Simulators Give Better Policy Gradients?
Hyung Ju Suh, Max Simchowitz, Kaiqing Zhang et al.
Does the Data Induce Capacity Control in Deep Learning?
Rubing Yang, Jialin Mao, Pratik Chaudhari
Domain Adaptation for Time Series Forecasting via Attention Sharing
Xiaoyong Jin, Youngsuk Park, Danielle Maddix et al.
Do More Negative Samples Necessarily Hurt In Contrastive Learning?
Pranjal Awasthi, Nishanth Dikkala, Pritish Kamath
Double Sampling Randomized Smoothing
Linyi Li, Jiawei Zhang, Tao Xie et al.
Doubly Robust Distributionally Robust Off-Policy Evaluation and Learning
Nathan Kallus, Xiaojie Mao, Kaiwen Wang et al.
DRAGONN: Distributed Randomized Approximate Gradients of Neural Networks
Zhuang Wang, Zhaozhuo Xu, Xinyu Wu et al.
DreamerPro: Reconstruction-Free Model-Based Reinforcement Learning with Prototypical Representations
Fei Deng, Ingook Jang, Sungjin Ahn
DRIBO: Robust Deep Reinforcement Learning via Multi-View Information Bottleneck
Jiameng Fan, Wenchao Li
DSTAGNN: Dynamic Spatial-Temporal Aware Graph Neural Network for Traffic Flow Forecasting
Shiyong Lan, Yitong Ma, Weikang Huang et al.
Dual Perspective of Label-Specific Feature Learning for Multi-Label Classification
Jun-Yi Hang, Min-Ling Zhang
Dynamic Regret of Online Markov Decision Processes
Peng Zhao, Long-Fei Li, Zhi-Hua Zhou
Dynamic Topic Models for Temporal Document Networks
Delvin Ce Zhang, Hady Lauw
DynaMixer: A Vision MLP Architecture with Dynamic Mixing
Ziyu Wang, Wenhao Jiang, Yiming M Zhu et al.
Easy Variational Inference for Categorical Models via an Independent Binary Approximation
Michael T Wojnowicz, Shuchin Aeron, Eric L Miller et al.
EAT-C: Environment-Adversarial sub-Task Curriculum for Efficient Reinforcement Learning
Shuang Ao, Tianyi Zhou, Jing Jiang et al.
EDEN: Communication-Efficient and Robust Distributed Mean Estimation for Federated Learning
Shay Vargaftik, Ran Ben Basat, Amit Portnoy et al.
Efficient Approximate Inference for Stationary Kernel on Frequency Domain
Yohan Jung, Kyungwoo Song, Jinkyoo Park
Efficient Computation of Higher-Order Subgraph Attribution via Message Passing
Ping Xiong, Thomas Schnake, Grégoire Montavon et al.
Efficient Distributionally Robust Bayesian Optimization with Worst-case Sensitivity
Sebastian Shenghong Tay, Chuan Sheng Foo, Urano Daisuke et al.
Efficient Learning for AlphaZero via Path Consistency
Dengwei Zhao, Shikui Tu, Lei Xu