Papers
Learning Generalizable Device Placement Algorithms for Distributed Machine Learning
ravichandra addanki, Shaileshh Bojja Venkatakrishnan, Shreyan Gupta et al.
Learning Hawkes Processes from a handful of events
Farnood Salehi, William Trouleau, Matthias Grossglauser et al.
Learning Hierarchical Priors in VAEs
Alexej Klushyn, Nutan Chen, Richard Kurle et al.
Learning Imbalanced Datasets with Label-Distribution-Aware Margin Loss
Kaidi Cao, Colin Wei, Adrien Gaidon et al.
Learning in Generalized Linear Contextual Bandits with Stochastic Delays
Zhengyuan Zhou, Renyuan Xu, Jose Blanchet
Learning-In-The-Loop Optimization: End-To-End Control And Co-Design Of Soft Robots Through Learned Deep Latent Representations
Andrew Spielberg, Allan Zhao, Yuanming Hu et al.
Learning Latent Process from High-Dimensional Event Sequences via Efficient Sampling
Qitian Wu, Zixuan Zhang, Xiaofeng Gao et al.
Learning Local Search Heuristics for Boolean Satisfiability
Emre Yolcu, Barnabas Poczos
Learning low-dimensional state embeddings and metastable clusters from time series data
Yifan Sun, Yaqi Duan, Hao Gong et al.
Learning Macroscopic Brain Connectomes via Group-Sparse Factorization
Farzane Aminmansour, Andrew Patterson, Lei Le et al.
Learning Mean-Field Games
Xin Guo, Anran Hu, Renyuan Xu et al.
Learning Mixtures of Plackett-Luce Models from Structured Partial Orders
Zhibing Zhao, Lirong Xia
Learning Multiple Markov Chains via Adaptive Allocation
Mohammad Sadegh Talebi, Odalric-Ambrym Maillard
Learning Nearest Neighbor Graphs from Noisy Distance Samples
Blake Mason, Ardhendu Tripathy, Robert Nowak
Learning Neural Networks with Adaptive Regularization
Han Zhao, Yao-Hung Hubert Tsai, Ruslan Salakhutdinov et al.
Learning New Tricks From Old Dogs: Multi-Source Transfer Learning From Pre-Trained Networks
Joshua Lee, Prasanna Sattigeri, Gregory Wornell
Learning Non-Convergent Non-Persistent Short-Run MCMC Toward Energy-Based Model
Erik Nijkamp, Mitch Hill, Song-Chun Zhu et al.
Learning nonlinear level sets for dimensionality reduction in function approximation
Guannan Zhang, Jiaxin Zhang, Jacob Hinkle
Learning Nonsymmetric Determinantal Point Processes
Mike Gartrell, Victor-Emmanuel Brunel, Elvis Dohmatob et al.
Learning Object Bounding Boxes for 3D Instance Segmentation on Point Clouds
Bo Yang, Jianan Wang, Ronald Clark et al.
Learning Perceptual Inference by Contrasting
Chi Zhang, Baoxiong Jia, Feng Gao et al.
Learning Positive Functions with Pseudo Mirror Descent
Yingxiang Yang, Haoxiang Wang, Negar Kiyavash et al.
Learning Representations by Maximizing Mutual Information Across Views
Philip Bachman, R Devon Hjelm, William Buchwalter
Learning Representations for Time Series Clustering
Qianli Ma, Jiawei Zheng, Sen Li et al.