Papers
Discount Factor as a Regularizer in Reinforcement Learning
Ron Amit, Ron Meir, Kamil Ciosek
Discriminative Adversarial Search for Abstractive Summarization
Thomas Scialom, Paul-Alexis Dray, Sylvain Lamprier et al.
Discriminative Jackknife: Quantifying Uncertainty in Deep Learning via Higher-Order Influence Functions
Ahmed Alaa, Mihaela Van Der Schaar
Disentangling Trainability and Generalization in Deep Neural Networks
Lechao Xiao, Jeffrey Pennington, Samuel Schoenholz
Dispersed Exponential Family Mixture VAEs for Interpretable Text Generation
Wenxian Shi, Hao Zhou, Ning Miao et al.
Distance Metric Learning with Joint Representation Diversification
Xu Chu, Yang Lin, Yasha Wang et al.
Distinguishing Cause from Effect Using Quantiles: Bivariate Quantile Causal Discovery
Natasa Tagasovska, Valérie Chavez-Demoulin, Thibault Vatter
Distributed Online Optimization over a Heterogeneous Network with Any-Batch Mirror Descent
Nima Eshraghi, Ben Liang
Distributionally Robust Policy Evaluation and Learning in Offline Contextual Bandits
Nian Si, Fan Zhang, Zhengyuan Zhou et al.
Distribution Augmentation for Generative Modeling
Heewoo Jun, Rewon Child, Mark Chen et al.
Divide and Conquer: Leveraging Intermediate Feature Representations for Quantized Training of Neural Networks
Ahmed Taha Elthakeb, Prannoy Pilligundla, Fatemeh Mireshghallah et al.
Divide, Conquer, and Combine: a New Inference Strategy for Probabilistic Programs with Stochastic Support
Yuan Zhou, Hongseok Yang, Yee Whye Teh et al.
Does label smoothing mitigate label noise?
Michal Lukasik, Srinadh Bhojanapalli, Aditya Menon et al.
Does the Markov Decision Process Fit the Data: Testing for the Markov Property in Sequential Decision Making
Chengchun Shi, Runzhe Wan, Rui Song et al.
Do GANs always have Nash equilibria?
Farzan Farnia, Asuman Ozdaglar
Domain Adaptive Imitation Learning
Kuno Kim, Yihong Gu, Jiaming Song et al.
Domain Aggregation Networks for Multi-Source Domain Adaptation
Junfeng Wen, Russell Greiner, Dale Schuurmans
Don’t Waste Your Bits! Squeeze Activations and Gradients for Deep Neural Networks via TinyScript
Fangcheng Fu, Yuzheng Hu, Yihan He et al.
Do RNN and LSTM have Long Memory?
Jingyu Zhao, Feiqing Huang, Jia Lv et al.
Double-Loop Unadjusted Langevin Algorithm
Paul Rolland, Armin Eftekhari, Ali Kavis et al.
Double Reinforcement Learning for Efficient and Robust Off-Policy Evaluation
Nathan Kallus, Masatoshi Uehara
Double Trouble in Double Descent: Bias and Variance(s) in the Lazy Regime
Stéphane D’Ascoli, Maria Refinetti, Giulio Biroli et al.
Doubly robust off-policy evaluation with shrinkage
Yi Su, Maria Dimakopoulou, Akshay Krishnamurthy et al.
Doubly Stochastic Variational Inference for Neural Processes with Hierarchical Latent Variables
Qi Wang, Herke Van Hoof