JMLR - volume 19 - 2018 论文列表 |
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Volume 19, 2018
Mariano Tepper Anirvan M. Sengupta Dmitri B. Chklovskii
Improved Asynchronous Parallel Optimization Analysis for Stochastic Incremental Methods.Rémi Leblond Fabian Pedregosa Simon Lacoste-Julien
Robust PCA by Manifold Optimization. A Random Matrix Analysis and Improvement of Semi-Supervised Learning for Large Dimensional Data. Online Bootstrap Confidence Intervals for the Stochastic Gradient Descent Estimator.Yixin Fang Jinfeng Xu Lei Yang
A Note on Quickly Sampling a Sparse Matrix with Low Rank Expectation.Karl Rohe Jun Tao Xintian Han Norbert Binkiewicz
Using Side Information to Reliably Learn Low-Rank Matrices from Missing and Corrupted Observations.Kai-Yang Chiang Inderjit S. Dhillon Cho-Jui Hsieh
Sparse Estimation in Ising Model via Penalized Monte Carlo Methods.Blazej Miasojedow Wojciech Rejchel
An efficient distributed learning algorithm based on effective local functional approximations.Dhruv Mahajan Nikunj Agrawal S. Sathiya Keerthi Sundararajan Sellamanickam Léon Bottou
Optimal Bounds for Johnson-Lindenstrauss Transformations.Michael A. Burr Shuhong Gao Fiona Knoll
Scikit-Multiflow: A Multi-output Streaming Framework.Jacob Montiel Jesse Read Albert Bifet Talel Abdessalem
Optimal Quantum Sample Complexity of Learning Algorithms.Srinivasan Arunachalam Ronald de Wolf
The Implicit Bias of Gradient Descent on Separable Data.Daniel Soudry Elad Hoffer Mor Shpigel Nacson Suriya Gunasekar Nathan Srebro
Inverse Reinforcement Learning via Nonparametric Spatio-Temporal Subgoal Modeling.Adrian Sosic Elmar Rueckert Jan Peters Abdelhak M. Zoubir Heinz Koeppl
Multivariate Bayesian Structural Time Series Model.Jinwen Qiu S. Rao Jammalamadaka Ning Ning
Efficient Bayesian Inference of Sigmoidal Gaussian Cox Processes.Christian Donner Manfred Opper
Inference via Low-Dimensional Couplings.Alessio Spantini Daniele Bigoni Youssef M. Marzouk
Extrapolating Expected Accuracies for Large Multi-Class Problems.Charles Y. Zheng Rakesh Achanta Yuval Benjamini
Scaling up Data Augmentation MCMC via Calibration.Leo L. Duan James E. Johndrow David B. Dunson
Short-term Sparse Portfolio Optimization Based on Alternating Direction Method of Multipliers.Zhao-Rong Lai Pei-Yi Yang Liangda Fang Xiaotian Wu
Hinge-Minimax Learner for the Ensemble of Hyperplanes.Dolev Raviv Tamir Hazan Margarita Osadchy
Simple Classification Using Binary Data.Deanna Needell Rayan Saab Tina Woolf
A New and Flexible Approach to the Analysis of Paired Comparison Data.Ivo F. D. Oliveira Nir Ailon Ori Davidov
Maximum Selection and Sorting with Adversarial Comparators.Jayadev Acharya Moein Falahatgar Ashkan Jafarpour Alon Orlitsky Ananda Theertha Suresh
Theoretical Analysis of Cross-Validation for Estimating the Risk of the $k$-Nearest Neighbor Classifier.Alain Celisse Tristan Mary-Huard
On Semiparametric Exponential Family Graphical Models.Zhuoran Yang Yang Ning Han Liu
Modular Proximal Optimization for Multidimensional Total-Variation Regularization.Álvaro Barbero Jiménez Suvrit Sra
Fast MCMC Sampling Algorithms on Polytopes.Yuansi Chen Raaz Dwivedi Martin J. Wainwright Bin Yu
How Deep Are Deep Gaussian Processes?Matthew M. Dunlop Mark A. Girolami Andrew M. Stuart Aretha L. Teckentrup
Profile-Based Bandit with Unknown Profiles.Sylvain Lamprier Thibault Gisselbrecht Patrick Gallinari
Accelerating Cross-Validation in Multinomial Logistic Regression with $\ell_1$-Regularization.Tomoyuki Obuchi Yoshiyuki Kabashima
Covariances, Robustness, and Variational Bayes.Ryan Giordano Tamara Broderick Michael I. Jordan
Emergence of Invariance and Disentanglement in Deep Representations.Alessandro Achille Stefano Soatto
Design and Analysis of the NIPS 2016 Review Process.Nihar B. Shah Behzad Tabibian Krikamol Muandet Isabelle Guyon Ulrike von Luxburg
On Generalized Bellman Equations and Temporal-Difference Learning.Huizhen Yu Ashique Rupam Mahmood Richard S. Sutton
Harmonic Mean Iteratively Reweighted Least Squares for Low-Rank Matrix Recovery.Christian Kümmerle Juliane Sigl
On Tight Bounds for the Lasso. Random Forests, Decision Trees, and Categorical Predictors: The "Absent Levels" Problem. Kernel Distribution Embeddings: Universal Kernels, Characteristic Kernels and Kernel Metrics on Distributions.Carl-Johann Simon-Gabriel Bernhard Schölkopf
Markov Blanket and Markov Boundary of Multiple Variables. An Efficient and Effective Generic Agglomerative Hierarchical Clustering Approach. Connections with Robust PCA and the Role of Emergent Sparsity in Variational Autoencoder Models.Bin Dai Yu Wang John Aston Gang Hua David P. Wipf
Learning from Comparisons and Choices.Sahand Negahban Sewoong Oh Kiran Koshy Thekumparampil Jiaming Xu
State-by-state Minimax Adaptive Estimation for Nonparametric Hidden Markov Models. Local Rademacher Complexity-based Learning Guarantees for Multi-Task Learning.Niloofar Yousefi Yunwen Lei Marius Kloft Mansooreh Mollaghasemi Georgios C. Anagnostopoulos
The xyz algorithm for fast interaction search in high-dimensional data.Gian-Andrea Thanei Nicolai Meinshausen Rajen Dinesh Shah
Invariant Models for Causal Transfer Learning.Mateo Rojas-Carulla Bernhard Schölkopf Richard E. Turner Jonas Peters
Kernel Density Estimation for Dynamical Systems.Hanyuan Hang Ingo Steinwart Yunlong Feng Johan A. K. Suykens
A Spectral Approach for the Design of Experiments: Design, Analysis and Algorithms.Bhavya Kailkhura Jayaraman J. Thiagarajan Charvi Rastogi Pramod K. Varshney Peer-Timo Bremer
Goodness-of-Fit Tests for Random Partitions via Symmetric Polynomials. Distribution-Specific Hardness of Learning Neural Networks. A Direct Approach for Sparse Quadratic Discriminant Analysis.Binyan Jiang Xiangyu Wang Chenlei Leng
Parallelizing Spectrally Regularized Kernel Algorithms. Gradient Descent Learns Linear Dynamical Systems.Moritz Hardt Tengyu Ma Benjamin Recht
Generalized Rank-Breaking: Computational and Statistical Tradeoffs. Importance Sampling for Minibatches. OpenEnsembles: A Python Resource for Ensemble Clustering.Tom Ronan Shawn Anastasio Zhijie Qi Pedro Henrique S. Vieira Tavares Roman Sloutsky Kristen M. Naegle
Deep Hidden Physics Models: Deep Learning of Nonlinear Partial Differential Equations. Universal discrete-time reservoir computers with stochastic inputs and linear readouts using non-homogeneous state-affine systems.Lyudmila Grigoryeva Juan-Pablo Ortega
Reverse Iterative Volume Sampling for Linear Regression.Michal Derezinski Manfred K. Warmuth
Robust Synthetic Control.Muhammad J. Amjad Devavrat Shah Dennis Shen
ThunderSVM: A Fast SVM Library on GPUs and CPUs.Zeyi Wen Jiashuai Shi Qinbin Li Bingsheng He Jian Chen
Refining the Confidence Level for Optimistic Bandit Strategies. Distributed Proximal Gradient Algorithm for Partially Asynchronous Computer Clusters.Yi Zhou Yingbin Liang Yaoliang Yu Wei Dai Eric P. Xing
Dual Principal Component Pursuit.Manolis C. Tsakiris René Vidal
Streaming kernel regression with provably adaptive mean, variance, and regularization.Audrey Durand Odalric-Ambrym Maillard Joelle Pineau
ELFI: Engine for Likelihood-Free Inference.Jarno Lintusaari Henri Vuollekoski Antti Kangasrääsiö Kusti Skytén Marko Järvenpää Pekka Marttinen Michael U. Gutmann Aki Vehtari Jukka Corander Samuel Kaski
Regularized Optimal Transport and the Rot Mover's Distance.Arnaud Dessein Nicolas Papadakis Jean-Luc Rouas
Model-Free Trajectory-based Policy Optimization with Monotonic Improvement.Riad Akrour Abbas Abdolmaleki Hany Abdulsamad Jan Peters Gerhard Neumann
A Robust Learning Approach for Regression Models Based on Distributionally Robust Optimization.Ruidi Chen Ioannis Ch. Paschalidis
Statistical Analysis and Parameter Selection for Mapper.Mathieu Carrière Bertrand Michel Steve Oudot
Change-Point Computation for Large Graphical Models: A Scalable Algorithm for Gaussian Graphical Models with Change-Points. A Constructive Approach to $L_0$ Penalized Regression.Jian Huang Yuling Jiao Yanyan Liu Xiliang Lu
Experience Selection in Deep Reinforcement Learning for Control.Tim de Bruin Jens Kober Karl Tuyls Robert Babuska
Scalable Bayes via Barycenter in Wasserstein Space.Sanvesh Srivastava Cheng Li David B. Dunson
Patchwork Kriging for Large-scale Gaussian Process Regression. RSG: Beating Subgradient Method without Smoothness and Strong Convexity. Can We Trust the Bootstrap in High-dimensions? The Case of Linear Models.Noureddine El Karoui Elizabeth Purdom
A Hidden Absorbing Semi-Markov Model for Informatively Censored Temporal Data: Learning and Inference.Ahmed M. Alaa Mihaela van der Schaar
Approximate Submodularity and its Applications: Subset Selection, Sparse Approximation and Dictionary Selection. A Two-Stage Penalized Least Squares Method for Constructing Large Systems of Structural Equations.Chen Chen Min Ren Min Zhang Dabao Zhang
Numerical Analysis near Singularities in RBF Networks.Weili Guo Haikun Wei Yew-Soon Ong Jaime Rubio Hervas Junsheng Zhao Hai Wang Kanjian Zhang