Papers
660 papers found
PU Learning for Matrix Completion
Cho-Jui Hsieh, Nagarajan Natarajan, Inderjit Dhillon
PHOG: Probabilistic Model for Code
Pavol Bielik, Veselin Raychev, Martin Vechev
Learning Algorithms for Active Learning
Philip Bachman, Alessandro Sordoni, Adam Trischler
Fast Bellman Updates for Robust MDPs
Chin Pang Ho, Marek Petrik, Wolfram Wiesemann
Shape Constraints for Set Functions
Andrew Cotter, Maya Gupta, Heinrich Jiang et al.
FloWaveNet : A Generative Flow for Raw Audio
Sungwon Kim, Sang-Gil Lee, Jongyoon Song et al.
Remember and Forget for Experience Replay
Guido Novati, Petros Koumoutsakos
Good Initializations of Variational Bayes for Deep Models
Simone Rossi, Pietro Michiardi, Maurizio Filippone
Distribution calibration for regression
Hao Song, Tom Diethe, Meelis Kull et al.
Deep Factors for Forecasting
Yuyang Wang, Alex Smola, Danielle Maddix et al.
Learning Novel Policies For Tasks
Yunbo Zhang, Wenhao Yu, Greg Turk
Deep k-NN for Noisy Labels
Dara Bahri, Heinrich Jiang, Maya Gupta
Adversarial Robustness for Code
Pavol Bielik, Martin Vechev
On Coresets for Regularized Regression
Rachit Chhaya, Anirban Dasgupta, Supratim Shit
On Contrastive Learning for Likelihood-free Inference
Conor Durkan, Iain Murray, George Papamakarios
Learning to Branch for Multi-Task Learning
Pengsheng Guo, Chen-Yu Lee, Daniel Ulbricht
Set Functions for Time Series
Max Horn, Michael Moor, Christian Bock et al.
Individual Fairness for k-Clustering
Sepideh Mahabadi, Ali Vakilian
Bandits for BMO Functions
Tianyu Wang, Cynthia Rudin
Loss Function Search for Face Recognition
Xiaobo Wang, Shuo Wang, Cheng Chi et al.
Machine Unlearning for Random Forests
Jonathan Brophy, Daniel Lowd
Learning Bounds for Open-Set Learning
Zhen Fang, Jie Lu, Anjin Liu et al.
Active Slices for Sliced Stein Discrepancy
Wenbo Gong, Kaibo Zhang, Yingzhen Li et al.
Winograd Algorithm for AdderNet
Wenshuo Li, Hanting Chen, Mingqiang Huang et al.
Data Augmentation for Meta-Learning
Renkun Ni, Micah Goldblum, Amr Sharaf et al.