Papers
Scaling All-Goals Updates in Reinforcement Learning Using Convolutional Neural Networks
Fabio Pardo, Vitaly Levdik, Petar Kormushev
Adversarial Localized Energy Network for Structured Prediction
Pingbo Pan, Ping Liu, Yan Yan et al.
Overcoming Catastrophic Forgetting by Neuron-Level Plasticity Control
Inyoung Paik, Sangjun Oh, Taeyeong Kwak et al.
Linear Bandits with Feature Feedback
Urvashi Oswal, Aniruddha Bhargava, Robert Nowak
Uncorrected Least-Squares Temporal Difference with Lambda-Return
Takayuki Osogami
Cut-Based Graph Learning Networks to Discover Compositional Structure of Sequential Video Data
Kyoung-Woon On, Eun-Sol Kim, Yu-Jung Heo et al.
Weighted Automata Extraction from Recurrent Neural Networks via Regression on State Spaces
Takamasa Okudono, Masaki Waga, Taro Sekiyama et al.
Radial and Directional Posteriors for Bayesian Deep Learning
Changyong Oh, Kamil Adamczewski, Mijung Park
Maximum Likelihood Embedding of Logistic Random Dot Product Graphs
Luke J. O'Connor, Muriel Medard, Soheil Feizi
Brain-Mediated Transfer Learning of Convolutional Neural Networks
Satoshi Nishida, Yusuke Nakano, Antoine Blanc et al.
On the Anatomy of MCMC-Based Maximum Likelihood Learning of Energy-Based Models
Erik Nijkamp, Mitch Hill, Tian Han et al.
Reliable Multilabel Classification: Prediction with Partial Abstention
Vu-Linh Nguyen, Eyke Hullermeier
Bayesian Optimization for Categorical and Category-Specific Continuous Inputs
Dang Nguyen, Sunil Gupta, Santu Rana et al.
Pairwise Fairness for Ranking and Regression
Harikrishna Narasimhan, Andrew Cotter, Maya Gupta et al.
Efficiently Enumerating Substrings with Statistically Significant Frequencies of Locally Optimal Occurrences in Gigantic String
Atsuyoshi Nakamura, Ichigaku Takigawa, Hiroshi Mamitsuka
An Intrinsically-Motivated Approach for Learning Highly Exploring and Fast Mixing Policies
Mirco Mutti, Marcello Restelli
Learning Weighted Model Integration Distributions
Paolo Morettin, Samuel Kolb, Stefano Teso et al.
Self-Supervised Learning for Generalizable Out-of-Distribution Detection
Sina Mohseni, Mandar Pitale, JBS Yadawa et al.
Metareasoning in Modular Software Systems: On-the-Fly Configuration Using Reinforcement Learning with Rich Contextual Representations
Aditya Modi, Debadeepta Dey, Alekh Agarwal et al.
On Adaptivity in Information-Constrained Online Learning
Siddharth Mitra, Aditya Gopalan
Improved Knowledge Distillation via Teacher Assistant
Seyed Iman Mirzadeh, Mehrdad Farajtabar, Ang Li et al.
Differentiable Reasoning on Large Knowledge Bases and Natural Language
Pasquale Minervini, Matko Bošnjak, Tim Rocktäschel et al.
Deep Embedded Non-Redundant Clustering
Lukas Miklautz, Dominik Mautz, Muzaffer Can Altinigneli et al.
Regularized Wasserstein Means for Aligning Distributional Data
Liang Mi, Wen Zhang, Yalin Wang
Neural Inheritance Relation Guided One-Shot Layer Assignment Search
Rang Meng, Weijie Chen, Di Xie et al.