Papers
ASAP: Adaptive Structure Aware Pooling for Learning Hierarchical Graph Representations
Ekagra Ranjan, Soumya Sanyal, Partha Talukdar
Synthesizing Action Sequences for Modifying Model Decisions
Goutham Ramakrishnan, Yun Chan Lee, Aws Albarghouthi
How Should an Agent Practice?
Janarthanan Rajendran, Richard Lewis, Vivek Veeriah et al.
A New Burrows Wheeler Transform Markov Distance
Edward Raff, Charles Nicholas, Mark McLean
Temporal Network Embedding with High-Order Nonlinear Information
Zhenyu Qiu, Wenbin Hu, Jia Wu et al.
Stochastic Approximate Gradient Descent via the Langevin Algorithm
Yixuan Qiu, Xiao Wang
Diversified Bayesian Nonnegative Matrix Factorization
Qiao Maoying, Yu Jun, Liu Tongliang et al.
CAG: A Real-Time Low-Cost Enhanced-Robustness High-Transferability Content-Aware Adversarial Attack Generator
Huy Phan, Yi Xie, Siyu Liao et al.
Generalized Hidden Parameter MDPs:Transferable Model-Based RL in a Handful of Trials
Christian Perez, Felipe Petroski Such, Theofanis Karaletsos
A Bayesian Approach for Estimating Causal Effects from Observational Data
Johan Pensar, Topi Talvitie, Antti Hyttinen et al.
Motif-Matching Based Subgraph-Level Attentional Convolutional Network for Graph Classification
Hao Peng, Jianxin Li, Qiran Gong et al.
Achieving Fairness in the Stochastic Multi-Armed Bandit Problem
Vishakha Patil, Ganesh Ghalme, Vineet Nair et al.
Unsupervised Attributed Multiplex Network Embedding
Chanyoung Park, Donghyun Kim, Jiawei Han et al.
EvolveGCN: Evolving Graph Convolutional Networks for Dynamic Graphs
Aldo Pareja, Giacomo Domeniconi, Jie Chen et al.
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.