JMLR Volume 18

Averaged Collapsed Variational Bayes Inference
Katsuhiko Ishiguro, Issei Sato, Naonori Ueda; 18(1):1−29, 2017.

Scalable Influence Maximization for Multiple Products in Continuous-Time Diffusion Networks
Nan Du, Yingyu Liang, Maria-Florina Balcan, Manuel Gomez-Rodriguez, Hongyuan Zha, Le Song; 18(2):1−45, 2017.

Local algorithms for interactive clustering
Pranjal Awasthi, Maria Florina Balcan, Konstantin Voevodski; 18(3):1−35, 2017.

SnapVX: A Network-Based Convex Optimization Solver
David Hallac, Christopher Wong, Steven Diamond, Abhijit Sharang, Rok Sosič, Stephen Boyd, Jure Leskovec; 18(4):1−5, 2017.
[abs][pdf][bib]    [code][]

Communication-efficient Sparse Regression
Jason D. Lee, Qiang Liu, Yuekai Sun, Jonathan E. Taylor; 18(5):1−30, 2017.

Improving Variational Methods via Pairwise Linear Response Identities
Jack Raymond, Federico Ricci-Tersenghi; 18(6):1−36, 2017.

Distributed Sequence Memory of Multidimensional Inputs in Recurrent Networks
Adam S. Charles, Dong Yin, Christopher J. Rozell; 18(7):1−37, 2017.

Persistence Images: A Stable Vector Representation of Persistent Homology
Henry Adams, Tegan Emerson, Michael Kirby, Rachel Neville, Chris Peterson, Patrick Shipman, Sofya Chepushtanova, Eric Hanson, Francis Motta, Lori Ziegelmeier; 18(8):1−35, 2017.

Spectral Clustering Based on Local PCA
Ery Arias-Castro, Gilad Lerman, Teng Zhang; 18(9):1−57, 2017.

On Perturbed Proximal Gradient Algorithms
Yves F. Atchadé, Gersende Fort, Eric Moulines; 18(10):1−33, 2017.

Differential Privacy for Bayesian Inference through Posterior Sampling
Christos Dimitrakakis, Blaine Nelson, Zuhe Zhang, Aikaterini Mitrokotsa, Benjamin I. P. Rubinstein; 18(11):1−39, 2017.

Refinery: An Open Source Topic Modeling Web Platform
Daeil Kim, Benjamin F. Swanson, Michael C. Hughes, Erik B. Sudderth; 18(12):1−5, 2017.
[abs][pdf][bib]    [code][github]

Using Conceptors to Manage Neural Long-Term Memories for Temporal Patterns
Herbert Jaeger; 18(13):1−43, 2017.

Automatic Differentiation Variational Inference
Alp Kucukelbir, Dustin Tran, Rajesh Ranganath, Andrew Gelman, David M. Blei; 18(14):1−45, 2017.

Empirical Evaluation of Resampling Procedures for Optimising SVM Hyperparameters
Jacques Wainer, Gavin Cawley; 18(15):1−35, 2017.

A Unified Formulation and Fast Accelerated Proximal Gradient Method for Classification
Naoki Ito, Akiko Takeda, Kim-Chuan Toh; 18(16):1−49, 2017.

Imbalanced-learn: A Python Toolbox to Tackle the Curse of Imbalanced Datasets in Machine Learning
Guillaume Lemaître, Fernando Nogueira, Christos K. Aridas; 18(17):1−5, 2017.
[abs][pdf][bib]    [code][]

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