Papers
Proximity Preserving Binary Code Using Signed Graph-Cut
Inbal Lavi, Shai Avidan, Yoram Singer et al.
A Simple and Efficient Tensor Calculus
Sören Laue, Matthias Mitterreiter, Joachim Giesen
Improved Subsampled Randomized Hadamard Transform for Linear SVM
Zijian Lei, Liang Lan
Correcting Predictions for Approximate Bayesian Inference
Tomasz Kuśmierczyk, Joseph Sakaya, Arto Klami
Google Research Football: A Novel Reinforcement Learning Environment
Karol Kurach, Anton Raichuk, Piotr Stańczyk et al.
Learning MAX-SAT from Contextual Examples for Combinatorial Optimisation
Mohit Kumar, Samuel Kolb, Stefano Teso et al.
Stable Prediction with Model Misspecification and Agnostic Distribution Shift
Kun Kuang, Ruoxuan Xiong, Peng Cui et al.
Specifying Weight Priors in Bayesian Deep Neural Networks with Empirical Bayes
Ranganath Krishnan, Mahesh Subedar, Omesh Tickoo
Learning Student Networks with Few Data
Shumin Kong, Tianyu Guo, Shan You et al.
A Unified Framework for Knowledge Intensive Gradient Boosting: Leveraging Human Experts for Noisy Sparse Domains
Harsha Kokel, Phillip Odom, Shuo Yang et al.
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