Papers
Data-Efficient Augmentation for Training Neural Networks
Tian Yu Liu, Baharan Mirzasoleiman
Data-Efficient Pipeline for Offline Reinforcement Learning with Limited Data
Allen Nie, Yannis Flet-Berliac, Deon Jordan et al.
Data-Efficient Structured Pruning via Submodular Optimization
Marwa El Halabi, Suraj Srinivas, Simon Lacoste-Julien
Data-IQ: Characterizing subgroups with heterogeneous outcomes in tabular data
Nabeel Seedat, Jonathan Crabbé, Ioana Bica et al.
DataMUX: Data Multiplexing for Neural Networks
Vishvak Murahari, Carlos Jimenez, Runzhe Yang et al.
Dataset Distillation using Neural Feature Regression
Yongchao Zhou, Ehsan Nezhadarya, Jimmy Ba
Dataset Distillation via Factorization
Songhua Liu, Kai Wang, Xingyi Yang et al.
Dataset Inference for Self-Supervised Models
Adam Dziedzic, Haonan Duan, Muhammad Ahmad Kaleem et al.
DC-BENCH: Dataset Condensation Benchmark
Justin CUI, Ruochen Wang, Si Si et al.
DDXPlus: A New Dataset For Automatic Medical Diagnosis
Arsene Fansi Tchango, Rishab Goel, Zhi Wen et al.
Debiased Causal Tree: Heterogeneous Treatment Effects Estimation with Unmeasured Confounding
Caizhi Tang, Huiyuan Wang, Xinyu Li et al.
Debiased, Longitudinal and Coordinated Drug Recommendation through Multi-Visit Clinic Records
Hongda Sun, Shufang Xie, Shuqi Li et al.
Debiased Machine Learning without Sample-Splitting for Stable Estimators
Qizhao Chen, Vasilis Syrgkanis, Morgane Austern
Debiased Self-Training for Semi-Supervised Learning
Baixu Chen, Junguang Jiang, Ximei Wang et al.
Debiasing Graph Neural Networks via Learning Disentangled Causal Substructure
Shaohua Fan, Xiao Wang, Yanhu Mo et al.
Debugging and Explaining Metric Learning Approaches: An Influence Function Based Perspective
Ruofan Liu, Yun Lin, XIANGLIN YANG et al.
Decentralized, Communication- and Coordination-free Learning in Structured Matching Markets
Chinmay Maheshwari, Shankar Sastry, Eric Mazumdar
Decentralized Gossip-Based Stochastic Bilevel Optimization over Communication Networks
Shuoguang Yang, Xuezhou Zhang, Mengdi Wang
Decentralized Local Stochastic Extra-Gradient for Variational Inequalities
Aleksandr Beznosikov, Pavel Dvurechenskii, Anastasiia Koloskova et al.
Decentralized Training of Foundation Models in Heterogeneous Environments
Binhang Yuan, Yongjun He, Jared Davis et al.
Deciding What to Model: Value-Equivalent Sampling for Reinforcement Learning
Dilip Arumugam, Benjamin Van Roy
Decision-based Black-box Attack Against Vision Transformers via Patch-wise Adversarial Removal
Yucheng Shi, Yahong Han, Yu-an Tan et al.
Decision-Focused Learning without Decision-Making: Learning Locally Optimized Decision Losses
Sanket Shah, Kai Wang, Bryan Wilder et al.
Decision Trees with Short Explainable Rules
Victor Feitosa Souza, Ferdinando Cicalese, Eduardo Laber et al.
Decomposable Non-Smooth Convex Optimization with Nearly-Linear Gradient Oracle Complexity
Sally Dong, Haotian Jiang, Yin Tat Lee et al.