Papers
Distributionally Robust Policy Learning under Concept Drifts
Jingyuan Wang, Zhimei Ren, Ruohan Zhan et al.
Distributional Off-policy Evaluation with Bellman Residual Minimization
Sungee Hong, Zhengling Qi, Raymond K. W. Wong
Distributional Reinforcement Learning with Dual Expectile-Quantile Regression
Sami Jullien, Romain Deffayet, Jean-Michel Renders et al.
Distributional Surgery for Language Model Activations
Bao Nguyen, Binh Nguyen, Duy Nguyen et al.
Distribution-aware Fairness Learning in Medical Image Segmentation From A Control-Theoretic Perspective
Yujin Oh, Pengfei Jin, Sangjoon Park et al.
Distribution-Aware Mean Estimation under User-level Local Differential Privacy
Corentin Pla, Maxime Vono, Hugo Richard
Distribution-Aware Online Learning for Urban Spatiotemporal Forecasting on Streaming Data
Chengxin Wang, Gary Tan, Swagato Barman Roy et al.
Distribution Backtracking Builds A Faster Convergence Trajectory for Diffusion Distillation
Shengyuan Zhang, Ling Yang, Zejian Li et al.
Distribution-Consistency-Guided Multi-modal Hashing
Jin-Yu Liu, Xian-Ling Mao, Tian-Yi Che et al.
Distribution-Driven Dense Retrieval: Modeling Many-to-One Query-Document Relationship
Junfeng Kang, Rui Li, Qi Liu et al.
Distribution Estimation under the Infinity Norm
Aryeh Kontorovich, Amichai Painsky
Distribution-Free Data Uncertainty for Neural Network Regression
Domokos M. Kelen, Ádám Jung, Péter Kersch et al.
Distribution Free Tests for Model Selection Based on Maximum Mean Discrepancy with Estimated Parameters
Florian Brück, Jean-David Fermanian, Aleksey Min
Distribution-Free Uncertainty Quantification in Mechanical Ventilation Treatment: A Conformal Deep Q-Learning Framework
Niloufar Eghbali, Tuka Alhanai, Mohammad M. Ghassemi
Distribution-Guided Multi-Tracer Brain PET Synthesis from Structural MRI with Class-Conditioned Weighted Diffusion
Minhui Yu, David S. Lalush, Derek C. Monroe et al.
Distribution Optimization under Gaussian Hypothesis for Domain Adaptive Semantic Segmentation
Chen Liang, Weihua Chen, Xin Zhao et al.
Distribution Prompting: Understanding the Expressivity of Language Models Through the Next-Token Distributions They Can Produce
Haojin Wang, Zining Zhu, Freda Shi
Distribution Prototype Diffusion Learning for Open-set Supervised Anomaly Detection
Fuyun Wang, Tong Zhang, Yuanzhi Wang et al.
Distribution-Specific Agnostic Conditional Classification With Halfspaces
Jizhou Huang, Brendan Juba
DistRL: An Asynchronous Distributed Reinforcement Learning Framework for On-Device Control Agent
Taiyi Wang, Zhihao Wu, Jianheng Liu et al.
DiT4Edit: Diffusion Transformer for Image Editing
Kunyu Feng, Yue Ma, Bingyuan Wang et al.
DiT4SR: Taming Diffusion Transformer for Real-World Image Super-Resolution
Zheng-Peng Duan, Jiawei Zhang, Xin Jin et al.
DiTaiListener: Controllable High Fidelity Listener Video Generation with Diffusion
Maksim Siniukov, Di Chang, Minh Tran et al.
DiTAR: Diffusion Transformer Autoregressive Modeling for Speech Generation
Dongya Jia, Zhuo Chen, Jiawei Chen et al.