Papers
Deep Learning for Functional Data Analysis with Adaptive Basis Layers
Junwen Yao, Jonas Mueller, Jane-Ling Wang
Deeply-Debiased Off-Policy Interval Estimation
Chengchun Shi, Runzhe Wan, Victor Chernozhukov et al.
DeepReDuce: ReLU Reduction for Fast Private Inference
Nandan Kumar Jha, Zahra Ghodsi, Siddharth Garg et al.
Deep Reinforcement Learning amidst Continual Structured Non-Stationarity
Annie Xie, James Harrison, Chelsea Finn
DeepWalking Backwards: From Embeddings Back to Graphs
Sudhanshu Chanpuriya, Cameron Musco, Konstantinos Sotiropoulos et al.
Delving into Deep Imbalanced Regression
Yuzhe Yang, Kaiwen Zha, Yingcong Chen et al.
Demonstration-Conditioned Reinforcement Learning for Few-Shot Imitation
Christopher R. Dance, Julien Perez, Théo Cachet
Demystifying Inductive Biases for (Beta-)VAE Based Architectures
Dominik Zietlow, Michal Rolinek, Georg Martius
Density Constrained Reinforcement Learning
Zengyi Qin, Yuxiao Chen, Chuchu Fan
Descending through a Crowded Valley - Benchmarking Deep Learning Optimizers
Robin M Schmidt, Frank Schneider, Philipp Hennig
Detecting Rewards Deterioration in Episodic Reinforcement Learning
Ido Greenberg, Shie Mannor
Detection of Signal in the Spiked Rectangular Models
Ji Hyung Jung, Hye Won Chung, Ji Oon Lee
DFAC Framework: Factorizing the Value Function via Quantile Mixture for Multi-Agent Distributional Q-Learning
Wei-Fang Sun, Cheng-Kuang Lee, Chun-Yi Lee
DG-LMC: A Turn-key and Scalable Synchronous Distributed MCMC Algorithm via Langevin Monte Carlo within Gibbs
Vincent Plassier, Maxime Vono, Alain Durmus et al.
Dichotomous Optimistic Search to Quantify Human Perception
Julien Audiffren
Differentiable Dynamic Quantization with Mixed Precision and Adaptive Resolution
Zhaoyang Zhang, Wenqi Shao, Jinwei Gu et al.
Differentiable Particle Filtering via Entropy-Regularized Optimal Transport
Adrien Corenflos, James Thornton, George Deligiannidis et al.
Differentiable Sorting Networks for Scalable Sorting and Ranking Supervision
Felix Petersen, Christian Borgelt, Hilde Kuehne et al.
Differentiable Spatial Planning using Transformers
Devendra Singh Chaplot, Deepak Pathak, Jitendra Malik
Differentially Private Aggregation in the Shuffle Model: Almost Central Accuracy in Almost a Single Message
Badih Ghazi, Ravi Kumar, Pasin Manurangsi et al.
Differentially Private Bayesian Inference for Generalized Linear Models
Tejas Kulkarni, Joonas Jälkö, Antti Koskela et al.
Differentially-Private Clustering of Easy Instances
Edith Cohen, Haim Kaplan, Yishay Mansour et al.
Differentially Private Correlation Clustering
Mark Bun, Marek Elias, Janardhan Kulkarni
Differentially Private Densest Subgraph Detection
Dung Nguyen, Anil Vullikanti