Papers
Learning Collaborative Policies to Solve NP-hard Routing Problems
Minsu Kim, Jinkyoo Park, joungho kim
Learning Compact Representations of Neural Networks using DiscriminAtive Masking (DAM)
Jie Bu, Arka Daw, M. Maruf et al.
Learning Conjoint Attentions for Graph Neural Nets
Tiantian He, Yew Soon Ong, L Bai
Learning curves of generic features maps for realistic datasets with a teacher-student model
Bruno Loureiro, Cedric Gerbelot, Hugo Cui et al.
Learning Debiased and Disentangled Representations for Semantic Segmentation
Sanghyeok Chu, Dongwan Kim, Bohyung Han
Learning Debiased Representation via Disentangled Feature Augmentation
Jungsoo Lee, Eungyeup Kim, Juyoung Lee et al.
Learning Disentangled Behavior Embeddings
Changhao Shi, Sivan Schwartz, Shahar Levy et al.
Learning Distilled Collaboration Graph for Multi-Agent Perception
Yiming Li, Shunli Ren, Pengxiang Wu et al.
Learning Diverse Policies in MOBA Games via Macro-Goals
Yiming Gao, Bei Shi, Xueying Du et al.
Learning Domain Invariant Representations in Goal-conditioned Block MDPs
Beining Han, Chongyi Zheng, Harris Chan et al.
Learning Dynamic Graph Representation of Brain Connectome with Spatio-Temporal Attention
Byung-Hoon Kim, Jong Chul Ye, Jae-Jin Kim
Learning Equilibria in Matching Markets from Bandit Feedback
Meena Jagadeesan, Alexander Wei, Yixin Wang et al.
Learning Equivariant Energy Based Models with Equivariant Stein Variational Gradient Descent
Priyank Jaini, Lars Holdijk, Max Welling
Learning Fast-Inference Bayesian Networks
Vaidyanathan Peruvemba Ramaswamy, Stefan Szeider
Learning Frequency Domain Approximation for Binary Neural Networks
Yixing Xu, Kai Han, Chang Xu et al.
Learning from Inside: Self-driven Siamese Sampling and Reasoning for Video Question Answering
Weijiang Yu, Haoteng Zheng, Mengfei Li et al.
Learning Gaussian Mixtures with Generalized Linear Models: Precise Asymptotics in High-dimensions
Bruno Loureiro, Gabriele Sicuro, Cedric Gerbelot et al.
Learning Generalized Gumbel-max Causal Mechanisms
Guy Lorberbom, Daniel D. Johnson, Chris J Maddison et al.
Learning Generative Vision Transformer with Energy-Based Latent Space for Saliency Prediction
Jing Zhang, Jianwen Xie, Nick Barnes et al.
Learning Graph Cellular Automata
Daniele Grattarola, Lorenzo Livi, Cesare Alippi
Learning Graph Models for Retrosynthesis Prediction
Vignesh Ram Somnath, Charlotte Bunne, Connor Coley et al.
Learning Hard Optimization Problems: A Data Generation Perspective
James Kotary, Ferdinando Fioretto, Pascal Van Hentenryck
Learning High-Precision Bounding Box for Rotated Object Detection via Kullback-Leibler Divergence
Xue Yang, Xiaojiang Yang, Jirui Yang et al.
Learning in Multi-Stage Decentralized Matching Markets
Xiaowu Dai, Michael I. Jordan
Learning in Non-Cooperative Configurable Markov Decision Processes
Giorgia Ramponi, Alberto Maria Metelli, Alessandro Concetti et al.