Proceedings of the 30th International Conference on Machine Learning, Cycle 2
ICML c2, 2013.

@proceedings{ICML-c2-2013,
	address       = "Atlanta, Georgia, USA",
	ee            = "http://jmlr.org/proceedings/papers/v28/",
	publisher     = "{JMLR.org}",
	series        = "{JMLR Proceedings}",
	title         = "{Proceedings of the 30th International Conference on Machine Learning, Cycle 2}",
	volume        = 28,
	year          = 2013,
}

Contents (42 items)

11 ×#learning
7 ×#modelling
5 ×#multi
4 ×#clustering
4 ×#optimisation
4 ×#topic
3 ×#framework
3 ×#matrix
3 ×#scalability
2 ×#algorithm

ICML-c2-2013-YangZ #process

Mixture of Mutually Exciting Processes for Viral Diffusion (SHY, HZ), pp. 1–9.

ICML-c2-2013-Lopez-PazHG #dependence #multi #process

Gaussian Process Vine Copulas for Multivariate Dependence (DLP, JMHL, ZG), pp. 10–18.

ICML-c2-2013-ValkoCM #optimisation #probability

Stochastic Simultaneous Optimistic Optimization (MV, AC, RM), pp. 19–27.

ICML-c2-2013-CarpentierM #integration #monte carlo #towards

Toward Optimal Stratification for Stratified Monte-Carlo Integration (AC, RM), pp. 28–36.

ICML-c2-2013-GongZLHY #algorithm #optimisation #problem

A General Iterative Shrinkage and Thresholding Algorithm for Non-convex Regularized Optimization Problems (PG, CZ, ZL, JH, JY), pp. 37–45.

ICML-c2-2013-TranPV #learning #multi

Thurstonian Boltzmann Machines: Learning from Multiple Inequalities (TT, DQP, SV), pp. 46–54.

ICML-c2-2013-KimVS #approximate #corpus #modelling #topic

A Variational Approximation for Topic Modeling of Hierarchical Corpora (DkK, GMV, LKS), pp. 55–63.

ICML-c2-2013-Goerg #analysis #component

Forecastable Component Analysis (GMG), pp. 64–72.

ICML-c2-2013-KrummenacherOB #learning #multi

Ellipsoidal Multiple Instance Learning (GK, CSO, JMB), pp. 73–81.

ICML-c2-2013-LeeKLS #approximate #matrix #rank

Local Low-Rank Matrix Approximation (JL, SK, GL, YS), pp. 82–90.

ICML-c2-2013-UrvoyCFN

Generic Exploration and K-armed Voting Bandits (TU, FC, RF, SN), pp. 91–99.

ICML-c2-2013-MinhBM #framework #learning #multi

A unifying framework for vector-valued manifold regularization and multi-view learning (HQM, LB, VM), pp. 100–108.

ICML-c2-2013-GaneshapillaiGL #learning

Learning Connections in Financial Time Series (GG, JVG, AL), pp. 109–117.

ICML-c2-2013-WangM #performance

Fast dropout training (SIW, CDM), pp. 118–126.

ICML-c2-2013-YangPK #optimisation #scalability #visualisation

Scalable Optimization of Neighbor Embedding for Visualization (ZY, JP, SK), pp. 127–135.

ICML-c2-2013-HanczarN #clustering

Precision-recall space to correct external indices for biclustering (BH, MN), pp. 136–144.

ICML-c2-2013-WulffUB #clustering

Monochromatic Bi-Clustering (SW, RU, SBD), pp. 145–153.

ICML-c2-2013-AlainO

Gated Autoencoders with Tied Input Weights (AD, OS), pp. 154–162.

ICML-c2-2013-Rebagliati #clustering #fault #normalisation #strict

Strict Monotonicity of Sum of Squares Error and Normalized Cut in the Lattice of Clusterings (NR), pp. 163–171.

ICML-c2-2013-HanL #estimation #matrix

Transition Matrix Estimation in High Dimensional Time Series (FH, HL), pp. 172–180.

ICML-c2-2013-WestonMY #clustering #ranking #sublinear

Label Partitioning For Sublinear Ranking (JW, AM, HY), pp. 181–189.

ICML-c2-2013-WangK13a #approach #message passing #problem

Subproblem-Tree Calibration: A Unified Approach to Max-Product Message Passing (HW, DK), pp. 190–198.

ICML-c2-2013-BardenetBKS #collaboration

Collaborative hyperparameter tuning (RB, MB, BK, MS), pp. 199–207.

ICML-c2-2013-CaiZH #framework #named #robust

SADA: A General Framework to Support Robust Causation Discovery (RC, ZZ, ZH), pp. 208–216.

ICML-c2-2013-SohnZLL #learning

Learning and Selecting Features Jointly with Point-wise Gated Boltzmann Machines (KS, GZ, CL, HL), pp. 217–225.

ICML-c2-2013-WenKEB

Sequential Bayesian Search (ZW, BK, BE, SB), pp. 226–234.

ICML-c2-2013-KyrillidisBCK

Sparse projections onto the simplex (ATK, SB, VC, CK), pp. 235–243.

ICML-c2-2013-ShalitWC #modelling #topic

Modeling Musical Influence with Topic Models (US, DW, GC), pp. 244–252.

ICML-c2-2013-DasBBG #automation #modelling #topic

Subtle Topic Models and Discovering Subtly Manifested Software Concerns Automatically (MKD, SB, CB, KG), pp. 253–261.

ICML-c2-2013-SalazarBGHC

Exploring the Mind: Integrating Questionnaires and fMRI (ES, RB, AG, AH, LC), pp. 262–270.

ICML-c2-2013-Tran-DinhKC #framework #graph #learning #matrix

A proximal Newton framework for composite minimization: Graph learning without Cholesky decompositions and matrix inversions (QTD, ATK, VC), pp. 271–279.

ICML-c2-2013-AroraGHMMSWZ #algorithm #modelling #topic

A Practical Algorithm for Topic Modeling with Provable Guarantees (SA, RG, YH, DMM, AM, DS, YW, MZ), pp. 280–288.

ICML-c2-2013-GopalY #distributed #modelling #scalability

Distributed training of Large-scale Logistic models (SG, YY), pp. 289–297.

ICML-c2-2013-RanganathWBX #adaptation #learning #probability

An Adaptive Learning Rate for Stochastic Variational Inference (RR, CW, DMB, EPX), pp. 298–306.

ICML-c2-2013-Telgarsky

Margins, Shrinkage, and Boosting (MT), pp. 307–315.

ICML-c2-2013-ChangKKZ #analysis #canonical #correlation #independence #kernel

Canonical Correlation Analysis based on Hilbert-Schmidt Independence Criterion and Centered Kernel Target Alignment (BC, UK, RK, JZ), pp. 316–324.

ICML-c2-2013-GolovinSMY #learning #ram #scalability

Large-Scale Learning with Less RAM via Randomization (DG, DS, HBM, MY), pp. 325–333.

ICML-c2-2013-ErmonGSS #integration #optimisation

Taming the Curse of Dimensionality: Discrete Integration by Hashing and Optimization (SE, CPG, AS, BS), pp. 334–342.

ICML-c2-2013-MaurerPR #learning #multi

Sparse coding for multitask and transfer learning (AM, MP, BRP), pp. 343–351.

ICML-c2-2013-Hui #modelling #visual notation

Direct Modeling of Complex Invariances for Visual Object Features (KYH), pp. 352–360.

ICML-c2-2013-MeentBWGW #learning #markov #modelling

Hierarchically-coupled hidden Markov models for learning kinetic rates from single-molecule data (JWvdM, JEB, FW, RLG, CW), pp. 361–369.

ICML-c2-2013-YangH #classification #learning

Activized Learning with Uniform Classification Noise (LY, SH), pp. 370–378.