Papers
Dash: Semi-Supervised Learning with Dynamic Thresholding
Yi Xu, Lei Shang, Jinxing Ye et al.
Data augmentation for deep learning based accelerated MRI reconstruction with limited data
Zalan Fabian, Reinhard Heckel, Mahdi Soltanolkotabi
Data Augmentation for Meta-Learning
Renkun Ni, Micah Goldblum, Amr Sharaf et al.
Data-efficient Hindsight Off-policy Option Learning
Markus Wulfmeier, Dushyant Rao, Roland Hafner et al.
Data-Free Knowledge Distillation for Heterogeneous Federated Learning
Zhuangdi Zhu, Junyuan Hong, Jiayu Zhou
Dataset Condensation with Differentiable Siamese Augmentation
Bo Zhao, Hakan Bilen
Dataset Dynamics via Gradient Flows in Probability Space
David Alvarez-Melis, Nicolò Fusi
Debiasing a First-order Heuristic for Approximate Bi-level Optimization
Valerii Likhosherstov, Xingyou Song, Krzysztof Choromanski et al.
Debiasing Model Updates for Improving Personalized Federated Training
Durmus Alp Emre Acar, Yue Zhao, Ruizhao Zhu et al.
Decentralized Riemannian Gradient Descent on the Stiefel Manifold
Shixiang Chen, Alfredo Garcia, Mingyi Hong et al.
Decentralized Single-Timescale Actor-Critic on Zero-Sum Two-Player Stochastic Games
Hongyi Guo, Zuyue Fu, Zhuoran Yang et al.
Deciding What to Learn: A Rate-Distortion Approach
Dilip Arumugam, Benjamin Van Roy
Decomposable Submodular Function Minimization via Maximum Flow
Kyriakos Axiotis, Adam Karczmarz, Anish Mukherjee et al.
Decomposed Mutual Information Estimation for Contrastive Representation Learning
Alessandro Sordoni, Nouha Dziri, Hannes Schulz et al.
Decoupling Exploration and Exploitation for Meta-Reinforcement Learning without Sacrifices
Evan Z Liu, Aditi Raghunathan, Percy Liang et al.
Decoupling Representation Learning from Reinforcement Learning
Adam Stooke, Kimin Lee, Pieter Abbeel et al.
Decoupling Value and Policy for Generalization in Reinforcement Learning
Roberta Raileanu, Rob Fergus
Deep Adaptive Design: Amortizing Sequential Bayesian Experimental Design
Adam Foster, Desi R Ivanova, Ilyas Malik et al.
Deep Coherent Exploration for Continuous Control
Yijie Zhang, Herke Van Hoof
Deep Continuous Networks
Nergis Tomen, Silvia-Laura Pintea, Jan Van Gemert
Deep Generative Learning via Schrödinger Bridge
Gefei Wang, Yuling Jiao, Qian Xu et al.
Deep kernel processes
Laurence Aitchison, Adam Yang, Sebastian W. Ober
Deep Latent Graph Matching
Tianshu Yu, Runzhong Wang, Junchi Yan et al.