Papers
Learning the Stein Discrepancy for Training and Evaluating Energy-Based Models without Sampling
Will Grathwohl, Kuan-Chieh Wang, Joern-Henrik Jacobsen et al.
Learning the Valuations of a $k$-demand Agent
Hanrui Zhang, Vincent Conitzer
Learning to Branch for Multi-Task Learning
Pengsheng Guo, Chen-Yu Lee, Daniel Ulbricht
Learning to Combine Top-Down and Bottom-Up Signals in Recurrent Neural Networks with Attention over Modules
Sarthak Mittal, Alex Lamb, Anirudh Goyal et al.
Learning to Encode Position for Transformer with Continuous Dynamical Model
Xuanqing Liu, Hsiang-Fu Yu, Inderjit Dhillon et al.
Learning to Learn Kernels with Variational Random Features
Xiantong Zhen, Haoliang Sun, Yingjun Du et al.
Learning to Navigate The Synthetically Accessible Chemical Space Using Reinforcement Learning
Sai Krishna Gottipati, Boris Sattarov, Sufeng Niu et al.
Learning to Rank Learning Curves
Martin Wistuba, Tejaswini Pedapati
Learning to Score Behaviors for Guided Policy Optimization
Aldo Pacchiano, Jack Parker-Holder, Yunhao Tang et al.
Learning to Simulate and Design for Structural Engineering
Kai-Hung Chang, Chin-Yi Cheng
Learning to Simulate Complex Physics with Graph Networks
Alvaro Sanchez-Gonzalez, Jonathan Godwin, Tobias Pfaff et al.
Learning To Stop While Learning To Predict
Xinshi Chen, Hanjun Dai, Yu Li et al.
Learning What to Defer for Maximum Independent Sets
Sungsoo Ahn, Younggyo Seo, Jinwoo Shin
Learning with Bounded Instance and Label-dependent Label Noise
Jiacheng Cheng, Tongliang Liu, Kotagiri Ramamohanarao et al.
Learning with Feature and Distribution Evolvable Streams
Zhen-Yu Zhang, Peng Zhao, Yuan Jiang et al.
Learning with Good Feature Representations in Bandits and in RL with a Generative Model
Tor Lattimore, Csaba Szepesvari, Gellert Weisz
Learning with Multiple Complementary Labels
Lei Feng, Takuo Kaneko, Bo Han et al.
LEEP: A New Measure to Evaluate Transferability of Learned Representations
Cuong Nguyen, Tal Hassner, Matthias Seeger et al.
Let’s Agree to Agree: Neural Networks Share Classification Order on Real Datasets
Guy Hacohen, Leshem Choshen, Daphna Weinshall
Leveraging Frequency Analysis for Deep Fake Image Recognition
Joel Frank, Thorsten Eisenhofer, Lea Schönherr et al.
Leveraging Procedural Generation to Benchmark Reinforcement Learning
Karl Cobbe, Chris Hesse, Jacob Hilton et al.
Lifted Disjoint Paths with Application in Multiple Object Tracking
Andrea Hornakova, Roberto Henschel, Bodo Rosenhahn et al.
Likelihood-free MCMC with Amortized Approximate Ratio Estimators
Joeri Hermans, Volodimir Begy, Gilles Louppe
Linear bandits with Stochastic Delayed Feedback
Claire Vernade, Alexandra Carpentier, Tor Lattimore et al.