Papers
Convergence of Gradient Descent on Separable Data
Mor Shpigel Nacson, Jason Lee, Suriya Gunasekar et al.
Batched Stochastic Bayesian Optimization via Combinatorial Constraints Design
Kevin K. Yang, Yuxin Chen, Alycia Lee et al.
ABCD-Strategy: Budgeted Experimental Design for Targeted Causal Structure Discovery
Raj Agrawal, Chandler Squires, Karren Yang et al.
Representation Learning on Graphs: A Reinforcement Learning Application
Sephora Madjiheurem, Laura Toni
Interpreting Black Box Predictions using Fisher Kernels
Rajiv Khanna, Been Kim, Joydeep Ghosh et al.
Efficient Bayes Risk Estimation for Cost-Sensitive Classification
Daniel Andrade, Yuzuru Okajima
Multitask Metric Learning: Theory and Algorithm
Boyu Wang, Hejia Zhang, Peng Liu et al.
Fixing Mini-batch Sequences with Hierarchical Robust Partitioning
Shengjie Wang, Wenruo Bai, Chandrashekhar Lavania et al.
Robustness Guarantees for Density Clustering
Heinrich Jiang, Jennifer Jang, Ofir Nachum
Sample Efficient Graph-Based Optimization with Noisy Observations
Thanh Tan Nguyen, Ali Shameli, Yasin Abbasi-Yadkori et al.
Recovery Guarantees For Quadratic Tensors With Sparse Observations
Hongyang Zhang, Vatsal Sharan, Moses Charikar et al.
Active Ranking with Subset-wise Preferences
Aadirupa Saha, Aditya Gopalan
Adversarial Learning of a Sampler Based on an Unnormalized Distribution
Chunyuan Li, Ke Bai, Jianqiao Li et al.
The LORACs Prior for VAEs: Letting the Trees Speak for the Data
Sharad Vikram, Matthew D. Hoffman, Matthew J. Johnson
Multiscale Gaussian Process Level Set Estimation
Shubhanshu Shekhar, Tara Javidi
Harmonizable mixture kernels with variational Fourier features
Zheyang Shen, Markus Heinonen, Samuel Kaski
Multi-Order Information for Working Set Selection of Sequential Minimal Optimization
Qimao Yang, Changrong Li, Jun Guo
Reparameterizing Distributions on Lie Groups
Luca Falorsi, Pim de Haan, Tim R. Davidson et al.
Size of Interventional Markov Equivalence Classes in random DAG models
Dmitriy Katz, Karthikeyan Shanmugam, Chandler Squires et al.
Database Alignment with Gaussian Features
Osman E. Dai, Daniel Cullina, Negar Kiyavash
Domain-Size Aware Markov Logic Networks
Happy Mittal, Ayush Bhardwaj, Vibhav Gogate et al.
Lifting high-dimensional non-linear models with Gaussian regressors
Christos Thrampoulidis, Ankit Singh Rawat
Online Learning in Kernelized Markov Decision Processes
Sayak Ray Chowdhury, Aditya Gopalan
Accelerating Imitation Learning with Predictive Models
Ching-An Cheng, Xinyan Yan, Evangelos Theodorou et al.