Papers
4,025 papers found
Understanding the Impact of Competing Events on Heterogeneous Treatment Effect Estimation from Time-to-Event Data
Alicia Curth, Mihaela van der Schaar
Uni6Dv2: Noise Elimination for 6D Pose Estimation
Mingshan Sun, Ye Zheng, Tianpeng Bao et al.
Unified Perspective on Probability Divergence via the Density-Ratio Likelihood: Bridging KL-Divergence and Integral Probability Metrics
Masahiro Kato, Masaaki Imaizumi, Kentaro Minami
Uniformly Conservative Exploration in Reinforcement Learning
Wanqiao Xu, Yecheng Ma, Kan Xu et al.
Unifying local and global model explanations by functional decomposition of low dimensional structures
Munir Hiabu, Joseph T. Meyer, Marvin N. Wright
Universal Agent Mixtures and the Geometry of Intelligence
Samuel Allen Alexander, David Quarel, Len Du et al.
Unsupervised representation learning with recognition-parametrised probabilistic models
William I. Walker, Hugo Soulat, Changmin Yu et al.
USIM Gate: UpSampling Module for Segmenting Precise Boundaries concerning Entropy
Kyungsu Lee, Haeyun Lee, Jae Youn Hwang
Using Sliced Mutual Information to Study Memorization and Generalization in Deep Neural Networks
Shelvia Wongso, Rohan Ghosh, Mehul Motani
Variational Boosted Soft Trees
Tristan Cinquin, Tammo Rukat, Philipp Schmidt et al.
Variational Inference for Neyman-Scott Processes
Chengkuan Hong, Christian Shelton
Vector Optimization with Stochastic Bandit Feedback
Cagin Ararat, Cem Tekin
Vector Quantized Time Series Generation with a Bidirectional Prior Model
Daesoo Lee, Sara Malacarne, Erlend Aune
Wasserstein Distributional Learning via Majorization-Minimization
Chengliang Tang, Nathan Lenssen, Ying Wei et al.
Wasserstein Distributionally Robust Linear-Quadratic Estimation under Martingale Constraints
Kyriakos Lotidis, Nicholas Bambos, Jose Blanchet et al.
Weisfeiler and Leman go Hyperbolic: Learning Distance Preserving Node Representations
Giannis Nikolentzos, Michail Chatzianastasis, Michalis Vazirgiannis
Who Should Predict? Exact Algorithms For Learning to Defer to Humans
Hussein Mozannar, Hunter Lang, Dennis Wei et al.
A Bandit Model for Human-Machine Decision Making with Private Information and Opacity
Sebastian Bordt, Ulrike Von Luxburg
A Bayesian Approach for Stochastic Continuum-armed Bandit with Long-term Constraints
Zai Shi, Atilla Eryilmaz
A Bayesian Model for Online Activity Sample Sizes
Thomas S. Richardson, Yu Liu, James Mcqueen et al.
A cautionary tale on fitting decision trees to data from additive models: generalization lower bounds
Yan Shuo Tan, Abhineet Agarwal, Bin Yu
Acceleration in Distributed Optimization under Similarity
Ye Tian, Gesualdo Scutari, Tianyu Cao et al.
Accurate Shapley Values for explaining tree-based models
Salim I. Amoukou, Tangi Salaün, Nicolas Brunel
A Class of Geometric Structures in Transfer Learning: Minimax Bounds and Optimality
Xuhui Zhang, Jose Blanchet, Soumyadip Ghosh et al.