Papers
Total Stability of SVMs and Localized SVMs
Hannes Köhler, Andreas Christmann
Towards An Efficient Approach for the Nonconvex lp Ball Projection: Algorithm and Analysis
Xiangyu Yang, Jiashan Wang, Hao Wang
Towards Practical Adam: Non-Convexity, Convergence Theory, and Mini-Batch Acceleration
Congliang Chen, Li Shen, Fangyu Zou et al.
Toward Understanding Convolutional Neural Networks from Volterra Convolution Perspective
Tenghui Li, Guoxu Zhou, Yuning Qiu et al.
Training and Evaluation of Deep Policies Using Reinforcement Learning and Generative Models
Ali Ghadirzadeh, Petra Poklukar, Karol Arndt et al.
Training Two-Layer ReLU Networks with Gradient Descent is Inconsistent
David Holzmüller, Ingo Steinwart
Transfer Learning in Information Criteria-based Feature Selection
Shaohan Chen, Nikolaos V. Sahinidis, Chuanhou Gao
Tree-Based Models for Correlated Data
Assaf Rabinowicz, Saharon Rosset
Tree-based Node Aggregation in Sparse Graphical Models
Ines Wilms, Jacob Bien
Tree-Values: Selective Inference for Regression Trees
Anna C. Neufeld, Lucy L. Gao, Daniela M. Witten
Truncated Emphatic Temporal Difference Methods for Prediction and Control
Shangtong Zhang, Shimon Whiteson
Two-mode Networks: Inference with as Many Parameters as Actors and Differential Privacy
Qiuping Wang, Ting Yan, Binyan Jiang et al.
Two-Sample Testing on Ranked Preference Data and the Role of Modeling Assumptions
Charvi Rastogi, Sivaraman Balakrishnan, Nihar B. Shah et al.
Unbiased estimators for random design regression
Michał Dereziński, Manfred K. Warmuth, Daniel Hsu
Under-bagging Nearest Neighbors for Imbalanced Classification
Hanyuan Hang, Yuchao Cai, Hanfang Yang et al.
Underspecification Presents Challenges for Credibility in Modern Machine Learning
Alexander D'Amour, Katherine Heller, Dan Moldovan et al.
Uniform deconvolution for Poisson Point Processes
Anna Bonnet, Claire Lacour, Franck Picard et al.
Universal Approximation in Dropout Neural Networks
Oxana A. Manita, Mark A. Peletier, Jacobus W. Portegies et al.
Universal Approximation of Functions on Sets
Edward Wagstaff, Fabian B. Fuchs, Martin Engelcke et al.
Universal Approximation Theorems for Differentiable Geometric Deep Learning
Anastasis Kratsios, Léonie Papon
Unlabeled Data Help in Graph-Based Semi-Supervised Learning: A Bayesian Nonparametrics Perspective
Daniel Sanz-Alonso, Ruiyi Yang
Using Active Queries to Infer Symmetric Node Functions of Graph Dynamical Systems
Abhijin Adiga, Chris J. Kuhlman, Madhav V. Marathe et al.
Using Shapley Values and Variational Autoencoders to Explain Predictive Models with Dependent Mixed Features
Lars H. B. Olsen, Ingrid K. Glad, Martin Jullum et al.
Variance Reduced EXTRA and DIGing and Their Optimal Acceleration for Strongly Convex Decentralized Optimization
Huan Li, Zhouchen Lin, Yongchun Fang
Variational Inference in high-dimensional linear regression
Sumit Mukherjee, Subhabrata Sen