Wednesday, June 19

ICML Videos Link

 

8:30 to 10:00,

Keynote Speaker: Vincent Vanhoucke

 

Wednesday, June 19, 10:30 to 12:10

Track A: Invited Orals

Session Chair: Michael Littman 

Room: International 7, 8, 9, 10

 

Webcast Link 

 

Classic Paper Prize Talk: Semi-supervised learning using gaussian fields and harmonic functions, ICML 2003, by Xiaojin (Jerry) Zhu, Zoubin Ghahramani, and John Lafferty

 

Classic Paper Prize Talk: Online convex programming and generalized infinitesimal gradient ascent, ICML 2003, by Martin Zinkevich

 

What do we learn from Kaggle competitions?,
Ben Hamner
abstract

 

Machine Learning and Natural Langauge Processing
Percy Liang
abstract/bio

 

394, Large-Scale Bandit Problems and KWIK Learning,
Jacob Abernethy; Kareem Amin; Michael Kearns; Moez Draief
abstract/pdf/supplementary

 

Wednesday, June 19, 10:30 to 12:10

Track B: Optimization

Session Chair: Fei Sha

Room: International 4, 5

 

48, Stochastic Gradient Descent for Non-smooth Optimization: Convergence Results and Optimal Averaging Schemes,
Ohad Shamir; Tong Zhang
abstract/pdf

 

232, Optimal rates for stochastic convex optimization under Tsybakov noise condition,
Aaditya Ramdas; Aarti Singh
abstract/pdf/supplementary

 

918, Fast Semidifferential-based Submodular Function Optimization,
Rishabh Iyer; Stefanie Jegelka; Jeff Bilmes
abstract/pdf/supplementary

 

612, A proximal Newton framework for composite minimization: Graph learning without Cholesky decompositions and matrix inversions,
Quoc Tran Dinh; Anastasios Kyrillidis; Volkan Cevher
abstract/pdf/supplementary

 

Spotlight Presentations:

 

1008, Mini-Batch Primal and Dual Methods for SVMs,
Martin Takac; Avleen Bijral; Peter Richtarik; Nati Srebro
abstract/pdf/supplementary

 

53, Stochastic Alternating Direction Method of Multipliers,
Hua Ouyang; Niao He; Long Tran; Alexander Gray
abstract/pdf/supplementary

 

884, Optimization with First-Order Surrogate Functions,
Julien Mairal
abstract/pdf/supplementary

 

41, Fast Probabilistic Optimization from Noisy Gradients,
Philipp Hennig
abstract/pdf

 

Wednesday, June 19, 10:30 to 12:10

Track C: Clustering

Session Chair: Maya Gupta 

Room: International 1, 2, 3

 

691, A Local Algorithm for Finding Well-Connected Clusters,
Silvio Lattanzi; Vahab Mirrokni; Zeyuan Allen Zhu
abstract/pdf

 

550, Monochromatic Bi-Clustering ,
Sharon Wulff; Ruth Urner; Shai Ben-David
abstract/pdf/supplementary

 

424, Constrained fractional set programs and their application in local clustering and community detection,
Thomas Bühler; Shyam Sundar Rangapuram; Simon Setzer; Matthias Hein
abstract/pdf/supplementary

 

987, Breaking the Small Cluster Barrier of Graph Clustering,
Nir Ailon; Yudong Chen; Huan Xu
abstract/pdf/supplementary

 

Spotlight Presentations:

 

555, Strict Monotonicity of Sum of Squares Error and Normalized Cut in the Lattice of Clusterings,
Nicola Rebagliati
abstract/pdf

 

190, Clustering and Learning Behaviors using a Sparse Latent Space,
Lui Montesano; Manuel Lopes; Javier Almingol
abstract/pdf/supplementary

 

545, Precision-recall space to correct external indices for biclustering,
Blaise Hanczar; Mohamed Nadif
abstract/pdf

 

1171, Semi-supervised Clustering by Input Pattern Assisted Pairwise Similarity Matrix Completion,
Jinfeng Yi; Rong Jin; Qi Qian; Anil Jain
abstract/pdf

 

Wednesday, June 19, 10:30 to 12:10

Track D: Learning Theory 1

Session Chair: Phil Long  

Room: International 6

 

644, Margins, Shrinkage and Boosting,
Matus Telgarsky
abstract/pdf/supplementary

 

849, Sharp Generalization Error Bounds for Randomly-projected Classifiers,
Robert Durrant; Ata Kaban
abstract/pdf

 

63, Risk Bounds and Learning Algorithms for the Regression Approach to Structured Output Prediction,
Sébastien Giguère; Francois Laviolette; Mario Marchand; Khadidja Sylla
abstract/pdf/supplementary

 

898, Collective Stability and Structured Prediction: Generalization from One Example,
Ben London; Bert Huang; Ben Taskar; Lise Getoor
abstract/pdf/supplementary

 

Spotlight Presentations:

 

54, Hierarchical Regularization Cascade for Joint Learning,
Alon Zweig; Daphna Weinshall
abstract/pdf/supplementary

 

443, Learning Fair Representations,
Rich Zemel; Yu Wu; Kevin Swersky; Toniann Pitassi; Cynthia Dwork
abstract/pdf/supplementary

 

173, Differentially Private Learning with Kernels,
Prateek Jain; Abhradeep Thakurta
abstract/pdf/supplementary

 

461, Rounding Methods for Discrete Linear Classification,
Yann Chevaleyre; Frederick Koriche; Jean-Daniel Zucker
abstract/pdf/supplementary

 

Wednesday, June 19, 2:00 to 3:40

Track A: Dimensionality Reduction and Semi-Supervised Learning

Session Chair: Jerry Zhu 

Room: International 7, 8, 9, 10

 

Webcast Link 

 

27, Squared-loss Mutual Information Regularization,
Gang Niu; Wittawat Jitkrittum; Bo Dai, ; Hirotaka Hachiya; Masashi Sugiyama
abstract/pdf/supplementary

 

509, Ellipsoidal Multiple Instance Learning,
Gabriel Krummenacher; Cheng Soon Ong; Joachim Buhmann
abstract/pdf/supplementary

 

933, Infinitesimal Annealing for Training Semi-Supervised Support Vector Machine,
Kohei Ogawa; Motoki Imamura; Ichiro Takeuchi; Masashi Sugiyama
abstract/pdf/supplementary

 

1108, Sparse Gaussian Conditional Random Fields: Algorithms, and Application to Energy Forecasting,
Matt Wytock; Zico Kolter
abstract/pdf/supplementary

 

1198, Adaptive Hamiltonian and Riemann Manifold Monte Carlo,
Ziyu Wang; Shakir Mohamed; De Freitas Nando
abstract/pdf

 

Wednesday, June 19, 2:00 to 3:40

Track B: Optimization and Integration

Session Chair: David Sontag

Room: International 4, 5

 

487, Stochastic Simultaneous Optimistic Optimization,
Michal Valko; Alexandra Carpentier; Remi Munos
abstract/pdf

 

36, Block-Coordinate Frank-Wolfe Optimization for Structural SVMs, Simon Lacoste-Julien; Martin Jaggi;  Mark Schmidt; Patrick Pletscher
abstract/pdf/supplementary

 

656, Taming the Curse of Dimensionality: Discrete Integration by Hashing and Optimization, Stefano Ermon; Carla Gomes; Ashish Sabharwal; Bart Selman
abstract/pdf/supplementary

 

Spotlight Presentations:

 

1116, Expensive Function Optimization with Stochastic Binary Outcomes,
Matthew Tesch; Jeff Schneider; Howie Choset
abstract/pdf

 

1047, O(logT) Projections for Stochastic Optimization of Smooth and Strongly Convex Functions,
Lijun Zhang; Tianbao Yang; Rong Jin; Xiaofei He
abstract/pdf/supplementary

 

275, Revisiting Frank-Wolfe: Projection-Free Sparse Convex Optimization,
Martin Jaggi
abstract/pdf/supplementary

 

1036, Algorithms for Direct 0–1 Loss Optimization in Binary Classification,
Tan Nguyen; Scott Sanner
abstract/pdf

 

488, Toward Optimal Stratification for Stratified Monte-Carlo Integration,
Alexandra Carpentier; Remi Munos
abstract/pdf

 

Wednesday, June 19, 2:00 to 3:40

Track C: Vision

Session Chair: Kilian Weinberger

Room: International 1, 2, 3

 

10, An Optimal Policy for Target Localization with Application to Electron Microscopy, Raphael Sznitman; Aurelien Lucchi; Peter Frazier; Bruno Jedynak; Pascal Fua
abstract/pdf

 

1115, Fast Image Tagging,
Minmin Chen; Alice Zheng; Kilian Weinberger
abstract/pdf

 

348, An Efficient Posterior Regularized Latent Variable Model for Interactive Sound Source Separation,
Nicholas Bryan; Gautham Mysore
abstract/pdf

 

Spotlight Presentations:

 

904, Max-Margin Multiple-Instance Dictionary Learning,
Xinggang Wang; Zhuowen Tu
abstract/pdf

 

761, Parameter Learning and Convergent Inference for Dense Random Fields,
Philipp Kraehenbuehl; Vladlen Koltun
abstract/pdf

 

418, Can We Recognize Tiger by Bus Images? _ Robust and Discriminative Self-Taught Image Categorization,
Hua Wang; Feiping Nie; Heng Huang
abstract/pdf/supplementary

 

886, Learning Spatio-Temporal Structure from RGB-D Videos for Human Activity Detection and Forecasting,
Hema Koppula; Ashutosh Saxena
abstract/pdf

 

15, A Spectral Learning Approach to Range-Only SLAM, Byron Boots;
Geoff Gordon
abstract/pdf/supplementary

 

726, Non-Linear Stationary Subspace Analysis with Application to Video Classification,
Mahsa Baktashmotlagh; Mehrtash Harandi; Abbas Bigdeli; Brian Lovell; Mathieu Salzmann
abstract/pdf/supplementary

 

776, On Compact Codes for Spatially Pooled Features,
Yangqing Jia; Oriol Vinyals; Trevor Darrell
abstract/pdf/supplementary

 

812, Analogy-preserving Semantic Embedding for Visual Object Categorization,
Sung Ju Hwang; Kristen Grauman; Fei Sha
abstract/pdf

 

Wednesday, June 19, 2:00 to 3:40

Track D: Learning Theory II

Session Chair: Mehryar Mohri

Room: International 1, 2, 3

 

1043, Exploiting Ontology Structures and Unlabeled Data for Learning,
Nina Balcan; Avrim Blum; Yishay Mansour
abstract/pdf/supplementary

 

952, One-Pass AUC Optimization, Wei Gao; Rong Jin; Shenghuo Zhu; Zhi-Hua Zhou
abstract/pdf

 

16, Near-Optimal Bounds for Cross-Validation via Loss Stability,
Ravi Kumar; Daniel Lokshtanov; Sergei Vassilvitskii; Andrea Vattani,
abstract/pdf

 

820, Algebraic classifiers: a generic approach to fast cross-validation,parallel training,
Michael Izbicki
abstract/pdf/supplementary

 

Spotlight Presentations:

 

1041, Top-k Selection based on Adaptive Sampling of Noisy Preferences,
Robert Busa-Fekete; Weiwei Cheng; Paul Weng; Eyke Huellermeier; Balazs Szorenyi
abstract/pdf/supplementary

 

319, Enhanced statistical rankings via targeted data collection,
Braxton Osting; Christoph Brune; Stanley Osher
abstract/pdf

 

138, Efficient Ranking from Pairwise Comparisons,
Fabian Wauthier; Michael Jordan; Nebojsa Jojic
abstract/pdf/supplementary

 

903, Stable Coactive Learning via Perturbation,
Karthik Raman; Thorsten Joachims,; Pannaga Shivaswamy; Tobias Schnabel
abstract/pdf/supplementary

 

 

Wednesday, June 19, 4:00 to 5:40

Track A: Crowd Sourcing and Large Scale Learning

Session Chair: Gert Lanckriet

Room: International 7, 8, 9, 10

 

Webcast Link 

 

96, Optimistic Knowledge Gradient Policy for Optimal Budget Allocation in Crowdsourcing,
Xi Chen; Qihang Lin; Dengyong Zhou
abstract/pdf/supplementary

 

926, Quantile Regression for Large-scale Applications,
Michael Mahoney; Jiyan Yang; Xiangrui Meng
abstract/pdf

 

621, Distributed training of Large-scale Logistic models,
Siddharth Gopal; Yiming Yang
abstract/pdf

 

570, Label Partitioning For Sublinear Ranking,
Jason Weston; Ameesh Makadia; Hector Yee
abstract/pdf

 

Spotlight Presentations:

 

213, Human Boosting,
Harsh Pareek; Pradeep Ravikumar
abstract/pdf/supplementary

 

655, Large-Scale Learning with Less RAM via Randomization,
Daniel Golovin; D. Sculley; Brendan McMahan; Michael Young
abstract/pdf

 

930, Robust Regression on MapReduce,
Michael Mahoney; Xiangrui Meng
abstract/pdf

 

366, Adaptive Task Assignment for Crowdsourced Classification,
Chien-Ju Ho; Shahin Jabbari; Jennifer Wortman Vaughan
abstract/pdf

 

Wednesday, June 19, 4:00 to 5:40

Track B: Kernel Methods

Session Chair: Percy Liang

Room: International 4, 5

 

751, Local Deep Kernel Learning for Efficient Non-linear SVM Prediction,
Cijo Jose; Prasoon Goyal; Parv Aggrwal; Manik Varma
abstract/pdf

 

361, Fastfood – Computing Hilbert Space Expansions in loglinear time,
Quoc Le; Tamas Sarlos; Alexander Smola
abstract/pdf/supplementary

 

1063, Smooth Operators and an RKHS Integration Approach,
Steffen Grunewalder; Gretton Arthur; John Shawe-Taylor
abstract/pdf/supplementary

 

895, Domain Adaptation under Target and Conditional Shift,
Kun Zhang; Bernhard Schoelkopf; Krikamol Muandet; Zhikun Wang
abstract/pdf/supplementary

 

Spotlight Presentations:

 

171, Learning Optimally Sparse Support Vector Machines,
Andrew Cotter; Shai Shalev-Shwartz; Nati Srebro
abstract/pdf/supplementary

 

262, A New Frontier of Kernel Design for Structured Data,
Kilho Shin
abstract/pdf

 

384 ,Characterizing the Representer Theorem,
Yaoliang Yu; Hao Cheng; Dale Schuurmans; Csaba Szepesvari
abstract/pdf

 

683, Covariate Shift in Hilber Space: A Solution Via Sorrogate Kernels,
Kai Zhang; Vincent Zheng; QIaojun Wang; James Kwok; Qiang Yang
abstract/pdf

 

Wednesday, June 19, 4:00 to 5:40

Track C: Matrix Factorization

Session Chair: Rich Zemel

 Room: Internationa 1, 2, 3

135, Fast Conical Hull Algorithms for Near-separable Non-negative Matrix Factorization,
Abhishek Kumar; Vikas Sindhwani; Prabhanjan Kambadur
abstract/pdf

 

278, General Functional Matrix Factorization Using Gradient Boosting,
Tianqi Chen; Hang Li; Qiang Yang; Yong Yu
abstract/pdf

 

981, Fast Max-Margin Matrix Factorization with Data Augmentation,
Minjie Xu; Jun Zhu; Bo Zhang
abstract/pdf/supplementary

 

513, Local Low-Rank Matrix Approximation,
Joonseok Lee; Seungyeon Kim; Guy Lebanon; Yoram Singer
abstract/pdf

 

Spotlight Presentations:

 

1174, Learning the beta-Divergence in Tweedie Compound Poisson Matrix Factorization Models,
Umut Simsekli; Yusuf Kenan Yilmaz; Ali Taylan Cemgil
abstract/pdf

 

343, ELLA: An Efficient Lifelong Learning Algorithm,
Paul Ruvolo; Eric Eaton
abstract/pdf/supplementary

 

772, Riemannian Similarity Learning,
Li Cheng
abstract/pdf

 

1120, Multiple-Source Cross Validation,
Krzysztof Geras; Charles Sutton
abstract/pdf

 

Wednesday, June 19, 4:00 to 5:40

Track D: Learning Theory 3

Session Chair: Jeff Bilmes

Room: International 6

 

675, Activized Learning with Uniform Classification Noise,
Liu Yang; Steve Hanneke
abstract/pdf

 

316, Efficient Active Learning of Halfspaces: an Aggressive Approach,
Alon Gonen; Sivan Sabato; Shai Shalev-Shwartz
abstract/pdf

 

1091, Selective sampling algorithms for cost-sensitive multiclass prediction,
Alekh Agarwa
abstract/pdf/supplementary

 

521, Generic Exploration and K-armed Voting Bandits,
Tanguy Urvoy; Fabrice Clerot; Raphael Feraud; Sami Naamane
abstract/pdf/supplementary

 

Spotlight Presentations:

 

433, Efficient Semi-supervised and Active Learning of Disjunctions,
Nina Balcan; Christopher Berlind; Steven Ehrlich; Yingyu Liang
abstract/pdf/supplementary

 

1158, Cost-sensitive Multiclass Classification Risk Bounds,
Bernardo Pires; Csaba Szepesvari; Mohammad Ghavamzadeh
abstract/pdf

 

308, Active Learning for Multi-Objective Optimization,
Marcela Zuluaga; Guillaume Sergent; Andreas Krause; Markus Pueschel
abstract/pdf/supplementary

 

90, Near-optimal Batch Mode Active Learning and Adaptive Submodular Optimization,
Yuxin Chen; Andreas Krause
abstract/pdf/supplementary

 

Wednesday, June 19, 6:00 to 8:00
ICML Banquet
Room: International 7, 8, 9, 10

 

Wednesday, June 19, 7:30 to 8:00
Poster Setup
Room: Skyline, 10th Floor

 

Wednesday, June 19, 8:00 to 10:00
Poster Session
Room: Skyline, 10th Floor