Papers
Adaptive Approximation and Generalization of Deep Neural Network with Intrinsic Dimensionality
Ryumei Nakada, Masaaki Imaizumi
Adaptive Rates for Total Variation Image Denoising
Francesco Ortelli, Sara van de Geer
Adaptive Smoothing for Path Integral Control
Dominik Thalmeier, Hilbert J. Kappen, Simone Totaro et al.
A Data Efficient and Feasible Level Set Method for Stochastic Convex Optimization with Expectation Constraints
Qihang Lin, Selvaprabu Nadarajah, Negar Soheili et al.
A determinantal point process for column subset selection
Ayoub Belhadji, Rémi Bardenet, Pierre Chainais
A General Framework for Consistent Structured Prediction with Implicit Loss Embeddings
Carlo Ciliberto, Lorenzo Rosasco, Alessandro Rudi
A General System of Differential Equations to Model First-Order Adaptive Algorithms
Andre Belotto da Silva, Maxime Gazeau
Agnostic Estimation for Phase Retrieval
Matey Neykov, Zhaoran Wang, Han Liu
A Group-Theoretic Framework for Data Augmentation
Shuxiao Chen, Edgar Dobriban, Jane H. Lee
AI Explainability 360: An Extensible Toolkit for Understanding Data and Machine Learning Models
Vijay Arya, Rachel K. E. Bellamy, Pin-Yu Chen et al.
AI-Toolbox: A C++ library for Reinforcement Learning and Planning (with Python Bindings)
Eugenio Bargiacchi, Diederik M. Roijers, Ann Nowé
algcomparison: Comparing the Performance of Graphical Structure Learning Algorithms with TETRAD
Joseph D. Ramsey, Daniel Malinsky, Kevin V. Bui
A Model of Fake Data in Data-driven Analysis
Xiaofan Li, Andrew B. Whinston
Ancestral Gumbel-Top-k Sampling for Sampling Without Replacement
Wouter Kool, Herke van Hoof, Max Welling
A New Class of Time Dependent Latent Factor Models with Applications
Sinead A. Williamson, Michael Minyi Zhang, Paul Damien
A Numerical Measure of the Instability of Mapper-Type Algorithms
Francisco Belchi, Jacek Brodzki, Matthew Burfitt et al.
Apache Mahout: Machine Learning on Distributed Dataflow Systems
Robin Anil, Gokhan Capan, Isabel Drost-Fromm et al.
apricot: Submodular selection for data summarization in Python
Jacob Schreiber, Jeffrey Bilmes, William Stafford Noble
A Regularization-Based Adaptive Test for High-Dimensional GLMs
Chong Wu, Gongjun Xu, Xiaotong Shen et al.
A Sober Look at the Unsupervised Learning of Disentangled Representations and their Evaluation
Francesco Locatello, Stefan Bauer, Mario Lucic et al.
A Sparse Semismooth Newton Based Proximal Majorization-Minimization Algorithm for Nonconvex Square-Root-Loss Regression Problems
Peipei Tang, Chengjing Wang, Defeng Sun et al.
A Statistical Learning Approach to Modal Regression
Yunlong Feng, Jun Fan, Johan A.K. Suykens
Asymptotic Consistency of $\alpha$-{R}ényi-Approximate Posteriors
Prateek Jaiswal, Vinayak Rao, Harsha Honnappa