Papers
4,025 papers found
GP-VAE: Deep Probabilistic Time Series Imputation
Vincent Fortuin, Dmitry Baranchuk, Gunnar Raetsch et al.
Gradient Descent with Early Stopping is Provably Robust to Label Noise for Overparameterized Neural Networks
Mingchen Li, Mahdi Soltanolkotabi, Samet Oymak
Graph Coarsening with Preserved Spectral Properties
Yu Jin, Andreas Loukas, Joseph JaJa
Graph DNA: Deep Neighborhood Aware Graph Encoding for Collaborative Filtering
Liwei Wu, Hsiang-Fu Yu, Nikhil Rao et al.
Greed Meets Sparsity: Understanding and Improving Greedy Coordinate Descent for Sparse Optimization
Huang Fang, Zhenan Fan, Yifan Sun et al.
Guaranteed Validity for Empirical Approaches to Adaptive Data Analysis
Ryan Rogers, Aaron Roth, Adam Smith et al.
Hamiltonian Monte Carlo Swindles
Dan Piponi, Matthew Hoffman, Pavel Sountsov
Hermitian matrices for clustering directed graphs: insights and applications
Mihai Cucuringu, Huan Li, He Sun et al.
High Dimensional Robust Sparse Regression
Liu Liu, Yanyao Shen, Tianyang Li et al.
How fine can fine-tuning be? Learning efficient language models
Evani Radiya-Dixit, Xin Wang
How To Backdoor Federated Learning
Eugene Bagdasaryan, Andreas Veit, Yiqing Hua et al.
Hyperbolic Manifold Regression
Gian Marconi, Carlo Ciliberto, Lorenzo Rosasco
Hypothesis Testing Interpretations and Renyi Differential Privacy
Borja Balle, Gilles Barthe, Marco Gaboardi et al.
Identifying and Correcting Label Bias in Machine Learning
Heinrich Jiang, Ofir Nachum
Importance Sampling via Local Sensitivity
Anant Raj, Cameron Musco, Lester Mackey
Improved Regret Bounds for Projection-free Bandit Convex Optimization
Dan Garber, Ben Kretzu
Improving Maximum Likelihood Training for Text Generation with Density Ratio Estimation
Yuxuan Song, Ning Miao, Hao Zhou et al.
Imputation estimators for unnormalized models with missing data
Masatoshi Uehara, Takeru Matsuda, Jae Kwang Kim
Independent Subspace Analysis for Unsupervised Learning of Disentangled Representations
Jan Stuehmer, Richard Turner, Sebastian Nowozin
Inference of Dynamic Graph Changes for Functional Connectome
Dingjue Ji, Junwei Lu, Yiliang Zhang et al.
Infinitely deep neural networks as diffusion processes
Stefano Peluchetti, Stefano Favaro
Integrals over Gaussians under Linear Domain Constraints
Alexandra Gessner, Oindrila Kanjilal, Philipp Hennig
Interpretable Companions for Black-Box Models
Danqing Pan, Tong Wang, Satoshi Hara
Interpretable Deep Gaussian Processes with Moments
Chi-Ken Lu, Scott Cheng-Hsin Yang, Xiaoran Hao et al.