Papers
4,025 papers found
Improved Approximation Algorithms for Individually Fair Clustering
Ali Vakilian, Mustafa Yalciner
Improving Attribution Methods by Learning Submodular Functions
Piyushi Manupriya, Tarun Ram Menta, Sakethanath N. Jagarlapudi et al.
Increasing the accuracy and resolution of precipitation forecasts using deep generative models
Ilan Price, Stephan Rasp
Independent Natural Policy Gradient always converges in Markov Potential Games
Roy Fox, Stephen M. Mcaleer, Will Overman et al.
Infinitely Deep Bayesian Neural Networks with Stochastic Differential Equations
Winnie Xu, Ricky T. Q. Chen, Xuechen Li et al.
Information-Theoretic Analysis of Epistemic Uncertainty in Bayesian Meta-learning
Sharu Theresa Jose, Sangwoo Park, Osvaldo Simeone
Investigating the Role of Negatives in Contrastive Representation Learning
Jordan Ash, Surbhi Goel, Akshay Krishnamurthy et al.
Is Bayesian Model-Agnostic Meta Learning Better than Model-Agnostic Meta Learning, Provably?
Lisha Chen, Tianyi Chen
Iterative Alignment Flows
Zeyu Zhou, Ziyu Gong, Pradeep Ravikumar et al.
Jointly Efficient and Optimal Algorithms for Logistic Bandits
Louis Faury, Marc Abeille, Kwang-Sung Jun et al.
k-experts - Online Policies and Fundamental Limits
Samrat Mukhopadhyay, Sourav Sahoo, Abhishek Sinha
k-Pareto Optimality-Based Sorting with Maximization of Choice
Jean Ruppert, Marharyta Aleksandrova, Thomas Engel
Label differential privacy via clustering
Hossein Esfandiari, Vahab Mirrokni, Umar Syed et al.
Lagrangian manifold Monte Carlo on Monge patches
Marcelo Hartmann, Mark Girolami, Arto Klami
Last Layer Marginal Likelihood for Invariance Learning
Pola Schwöbel, Martin Jørgensen, Sebastian W. Ober et al.
Learning and Generalization in Overparameterized Normalizing Flows
Kulin Shah, Amit Deshpande, Navin Goyal
Learning Competitive Equilibria in Exchange Economies with Bandit Feedback
Wenshuo Guo, Kirthevasan Kandasamy, Joseph Gonzalez et al.
Learning from an Exploring Demonstrator: Optimal Reward Estimation for Bandits
Wenshuo Guo, Kumar Krishna Agrawal, Aditya Grover et al.
Learning from Multiple Noisy Partial Labelers
Peilin Yu, Tiffany Ding, Stephen H. Bach
Learning Inconsistent Preferences with Gaussian Processes
Siu Lun Chau, Javier Gonzalez, Dino Sejdinovic
Learning in Stochastic Monotone Games with Decision-Dependent Data
Adhyyan Narang, Evan Faulkner, Dmitriy Drusvyatskiy et al.
Learning Interpretable, Tree-Based Projection Mappings for Nonlinear Embeddings
Arman S. Zharmagambetov, Miguel A. Carreira-Perpinan