Papers
Plug-in, Trainable Gate for Streamlining Arbitrary Neural Networks
Jaedeok Kim, Chiyoun Park, Hyun-Joo Jung et al.
Options of Interest: Temporal Abstraction with Interest Functions
Khimya Khetarpal, Martin Klissarov, Maxime Chevalier-Boisvert et al.
Being Optimistic to Be Conservative: Quickly Learning a CVaR Policy
Ramtin Keramati, Christoph Dann, Alex Tamkin et al.
Gradient Boosts the Approximate Vanishing Ideal
Hiroshi Kera, Yoshihiko Hasegawa
Nonlinear System Identification via Tensor Completion
Nikos Kargas, Nicholas D. Sidiropoulos
Large-Scale Multi-View Subspace Clustering in Linear Time
Zhao Kang, Wangtao Zhou, Zhitong Zhao et al.
Towards Oracle Knowledge Distillation with Neural Architecture Search
Minsoo Kang, Jonghwan Mun, Bohyung Han
Absum: Simple Regularization Method for Reducing Structural Sensitivity of Convolutional Neural Networks
Sekitoshi Kanai, Yasutoshi Ida, Yasuhiro Fujiwara et al.
More Accurate Learning of k-DNF Reference Classes
Brendan Juba, Hengxuan Li
InvNet: Encoding Geometric and Statistical Invariances in Deep Generative Models
Ameya Joshi, Minsu Cho, Viraj Shah et al.
Dynamic Instance Normalization for Arbitrary Style Transfer
Yongcheng Jing, Xiao Liu, Yukang Ding et al.
GraLSP: Graph Neural Networks with Local Structural Patterns
Yilun Jin, Guojie Song, Chuan Shi
Rank Aggregation via Heterogeneous Thurstone Preference Models
Tao Jin, Pan Xu, Quanquan Gu et al.
Long Short-Term Sample Distillation
Liang Jiang, Zujie Wen, Zhongping Liang et al.
Generative Exploration and Exploitation
Jiechuan Jiang, Zongqing Lu
Algorithmic Improvements for Deep Reinforcement Learning Applied to Interactive Fiction
Vishal Jain, William Fedus, Hugo Larochelle et al.
Representation Learning with Multiple Lipschitz-Constrained Alignments on Partially-Labeled Cross-Domain Data
Songlei Jian, Liang Hu, Longbing Cao et al.
Maximum Margin Multi-Dimensional Classification
Bin-Bin Jia, Min-Ling Zhang
Sequential Recommendation with Relation-Aware Kernelized Self-Attention
Mingi Ji, Weonyoung Joo, Kyungwoo Song et al.
DefogGAN: Predicting Hidden Information in the StarCraft Fog of War with Generative Adversarial Nets
Yonghyun Jeong, Hyunjin Choi, Byoungjip Kim et al.
An Efficient Explorative Sampling Considering the Generative Boundaries of Deep Generative Neural Networks
Giyoung Jeon, Haedong Jeong, Jaesik Choi
Bounding Regret in Empirical Games
Steven Jecmen, Arunesh Sinha, Zun Li et al.
Invariant Representations through Adversarial Forgetting
Ayush Jaiswal, Daniel Moyer, Greg Ver Steeg et al.
Maximizing Overall Diversity for Improved Uncertainty Estimates in Deep Ensembles
Siddhartha Jain, Ge Liu, Jonas Mueller et al.
Class Prior Estimation with Biased Positives and Unlabeled Examples
Shantanu Jain, Justin Delano, Himanshu Sharma et al.