Papers
Disentangling Disease-related Representation from Obscure for Disease Prediction
Chu-Ran Wang, Fei Gao, Fandong Zhang et al.
Disentangling Sources of Risk for Distributional Multi-Agent Reinforcement Learning
Kyunghwan Son, Junsu Kim, Sungsoo Ahn et al.
DisPFL: Towards Communication-Efficient Personalized Federated Learning via Decentralized Sparse Training
Rong Dai, Li Shen, Fengxiang He et al.
Distinguishing rule and exemplar-based generalization in learning systems
Ishita Dasgupta, Erin Grant, Tom Griffiths
Distributional Hamilton-Jacobi-Bellman Equations for Continuous-Time Reinforcement Learning
Harley E Wiltzer, David Meger, Marc G. Bellemare
Distributionally Robust $Q$-Learning
Zijian Liu, Qinxun Bai, Jose Blanchet et al.
Distribution Regression with Sliced Wasserstein Kernels
Dimitri Meunier, Massimiliano Pontil, Carlo Ciliberto
Divergence-Regularized Multi-Agent Actor-Critic
Kefan Su, Zongqing Lu
Diversified Adversarial Attacks based on Conjugate Gradient Method
Keiichiro Yamamura, Haruki Sato, Nariaki Tateiwa et al.
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