Papers
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
Differentially Private Quantiles
Jennifer Gillenwater, Matthew Joseph, Alex Kulesza
Differentially Private Query Release Through Adaptive Projection
Sergul Aydore, William Brown, Michael Kearns et al.
Differentially Private Sliced Wasserstein Distance
Alain Rakotomamonjy, Ralaivola Liva
Diffusion Earth Mover’s Distance and Distribution Embeddings
Alexander Y Tong, Guillaume Huguet, Amine Natik et al.
Diffusion Source Identification on Networks with Statistical Confidence
Quinlan E Dawkins, Tianxi Li, Haifeng Xu
Dimensionality Reduction for the Sum-of-Distances Metric
Zhili Feng, Praneeth Kacham, David Woodruff
Directed Graph Embeddings in Pseudo-Riemannian Manifolds
Aaron Sim, Maciej L Wiatrak, Angus Brayne et al.
Directional Bias Amplification
Angelina Wang, Olga Russakovsky
Directional Graph Networks
Dominique Beaini, Saro Passaro, Vincent Létourneau et al.
Disambiguation of Weak Supervision leading to Exponential Convergence rates
Vivien A Cabannnes, Francis Bach, Alessandro Rudi