Proceedings of the 21st International Conference on Machine Learning
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Carla E. Brodley
Proceedings of the 21st International Conference on Machine Learning
ICML, 2004.

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@proceedings{ICML-2004,
	address       = "Banff, Alberta, Canada",
	editor        = "Carla E. Brodley",
	publisher     = "{ACM}",
	series        = "{ACM International Conference Proceeding Series}",
	title         = "{Proceedings of the 21st International Conference on Machine Learning}",
	volume        = 69,
	year          = 2004,
}

Contents (117 items)

ICML-2004-AgarwalT #3d #learning
Learning to track 3D human motion from silhouettes (AA, BT).
ICML-2004-AhnCO #algorithm #multi
A multiplicative up-propagation algorithm (JHA, SC, JHO).
ICML-2004-AltunHS #classification #process #sequence
Gaussian process classification for segmenting and annotating sequences (YA, TH, AJS).
ICML-2004-AppiceCRF #multi #problem
Redundant feature elimination for multi-class problems (AA, MC, SR, PAF).
ICML-2004-BachLJ #algorithm #kernel #learning #multi
Multiple kernel learning, conic duality, and the SMO algorithm (FRB, GRGL, MIJ).
ICML-2004-BahamondeBDQLCAG #case study #learning #set
Feature subset selection for learning preferences: a case study (AB, GFB, JD, JRQ, OL, JJdC, JA, FG).
ICML-2004-BanerjeeDGM #analysis #estimation #exponential #product line
An information theoretic analysis of maximum likelihood mixture estimation for exponential families (AB, ISD, JG, SM).
ICML-2004-BasilicoH #collaboration
Unifying collaborative and content-based filtering (JB, TH).
ICML-2004-BaskiotisS #approach
C4.5 competence map: a phase transition-inspired approach (NB, MS).
ICML-2004-BilenkoBM #clustering #constraints #learning #metric
Integrating constraints and metric learning in semi-supervised clustering (MB, SB, RJM).
ICML-2004-BleiJ #process
Variational methods for the Dirichlet process (DMB, MIJ).
ICML-2004-BlumLRR #learning #random #using
Semi-supervised learning using randomized mincuts (AB, JDL, MRR, RR).
ICML-2004-BohteBG #classification #parametricity #polynomial
Nonparametric classification with polynomial MPMC cascades (SMB, MB, GZG).
ICML-2004-Bouckaert #classification #learning
Estimating replicability of classifier learning experiments (RRB).
ICML-2004-BrefeldS #learning
Co-EM support vector learning (UB, TS).
ICML-2004-Brinker #learning #ranking
Active learning of label ranking functions (KB).
ICML-2004-CaruanaNCK #library #modelling
Ensemble selection from libraries of models (RC, ANM, GC, AK).
ICML-2004-CastilloW #case study #comparative #learning #multi
A comparative study on methods for reducing myopia of hill-climbing search in multirelational learning (LPC, SW).
ICML-2004-ChangY #adaptation #clustering #linear #metric
Locally linear metric adaptation for semi-supervised clustering (HC, DYY).
ICML-2004-ChuGW #predict #visual notation
A graphical model for protein secondary structure prediction (WC, ZG, DLW).
ICML-2004-ClimerZ #approach #clustering
Take a walk and cluster genes: a TSP-based approach to optimal rearrangement clustering (SC, WZ).
ICML-2004-CollobertB
Links between perceptrons, MLPs and SVMs (RC, SB).
ICML-2004-ConitzerS #bound #communication #complexity #game studies #learning
Communication complexity as a lower bound for learning in games (VC, TS).
ICML-2004-CortesM #kernel
Distribution kernels based on moments of counts (CC, MM).
ICML-2004-CrammerC #optimisation
A needle in a haystack: local one-class optimization (KC, GC).
ICML-2004-DekelKS #classification #scalability
Large margin hierarchical classification (OD, JK, YS).
ICML-2004-DietterichAB #random
Training conditional random fields via gradient tree boosting (TGD, AA, YB).
ICML-2004-DingH #clustering
Linearized cluster assignment via spectral ordering (CHQD, XH).
ICML-2004-DingH04a #analysis #clustering #component
K-means clustering via principal component analysis (CHQD, XH).
ICML-2004-DSouzaVS
The Bayesian backfitting relevance vector machine (AD, SV, SS).
ICML-2004-EliazarP #learning #mobile #modelling #probability
Learning probabilistic motion models for mobile robots (AIE, RP).
ICML-2004-EsmeirM #algorithm #induction
Lookahead-based algorithms for anytime induction of decision trees (SE, SM).
ICML-2004-EspositoS #analysis #classification #monte carlo
A Monte Carlo analysis of ensemble classification (RE, LS).
ICML-2004-FernB #clustering #graph #problem
Solving cluster ensemble problems by bipartite graph partitioning (XZF, CEB).
ICML-2004-FernG #relational #reliability
Relational sequential inference with reliable observations (AF, RG).
ICML-2004-FerriFH #classification
Delegating classifiers (CF, PAF, JHO).
ICML-2004-Forman #classification #feature model #multi
A pitfall and solution in multi-class feature selection for text classification (GF).
ICML-2004-FrankK #multi #problem
Ensembles of nested dichotomies for multi-class problems (EF, SK).
ICML-2004-FungDBR #algorithm #kernel #performance #using
A fast iterative algorithm for fisher discriminant using heterogeneous kernels (GF, MD, JB, RBR).
ICML-2004-GabrilovichM #categorisation #feature model #using
Text categorization with many redundant features: using aggressive feature selection to make SVMs competitive with C4.5 (EG, SM).
ICML-2004-GaoWLC #approach #categorisation #learning #multi #robust
A MFoM learning approach to robust multiclass multi-label text categorization (SG, WW, CHL, TSC).
ICML-2004-Gilad-BachrachNT #algorithm #feature model
Margin based feature selection — theory and algorithms (RGB, AN, NT).
ICML-2004-GoldenbergM #learning #scalability
Tractable learning of large Bayes net structures from sparse data (AG, AWM).
ICML-2004-GramacyLM #parametricity #process
Parameter space exploration with Gaussian process trees (RBG, HKHL, WGM).
ICML-2004-GrossmanD #classification #learning #network
Learning Bayesian network classifiers by maximizing conditional likelihood (DG, PMD).
ICML-2004-HamLMS #kernel #reduction
A kernel view of the dimensionality reduction of manifolds (JH, DDL, SM, BS).
ICML-2004-HardinTA #feature model #linear
A theoretical characterization of linear SVM-based feature selection (DPH, IT, CFA).
ICML-2004-HerschtalR #optimisation #using
Optimising area under the ROC curve using gradient descent (AH, BR).
ICML-2004-HertzBW #clustering #distance
Boosting margin based distance functions for clustering (TH, ABH, DW).
ICML-2004-HuangYKL #classification #learning #scalability
Learning large margin classifiers locally and globally (KH, HY, IK, MRL).
ICML-2004-JakulinB #interactive #testing
Testing the significance of attribute interactions (AJ, IB).
ICML-2004-JamesS #learning #predict
Learning and discovery of predictive state representations in dynamical systems with reset (MRJ, SPS).
ICML-2004-JanodetNSS #grammar inference
Boosting grammatical inference with confidence oracles (JCJ, RN, MS, HMS).
ICML-2004-Jebara #kernel #multi
Multi-task feature and kernel selection for SVMs (TJ).
ICML-2004-JenkinsM #reduction
A spatio-temporal extension to Isomap nonlinear dimension reduction (OCJ, MJM).
ICML-2004-JinL #induction #robust
Robust feature induction for support vector machines (RJ, HL).
ICML-2004-KashimaT #algorithm #graph #kernel #learning #sequence
Kernel-based discriminative learning algorithms for labeling sequences, trees, and graphs (HK, YT).
ICML-2004-KerstingOR #relational
Bellman goes relational (KK, MvO, LDR).
ICML-2004-KimK #feature model
Gradient LASSO for feature selection (YK, JK).
ICML-2004-KokV
Sparse cooperative Q-learning (JRK, NAV).
ICML-2004-KoppelS #classification #problem #verification
Authorship verification as a one-class classification problem (MK, JS).
ICML-2004-KrauseS
Leveraging the margin more carefully (NK, YS).
ICML-2004-LaffertyZL #clique #kernel #random #representation
Kernel conditional random fields: representation and clique selection (JDL, XZ, YL).
ICML-2004-LawrenceP #learning
Learning to learn with the informative vector machine (NDL, JCP).
ICML-2004-LebanonL #classification #multi
Hyperplane margin classifiers on the multinomial manifold (GL, JDL).
ICML-2004-LeeWZB #perspective #probability
Probabilistic tangent subspace: a unified view (JL, JW, CZ, ZB).
ICML-2004-LiMO #category theory #clustering
Entropy-based criterion in categorical clustering (TL, SM, MO).
ICML-2004-LingYWZ #low cost
Decision trees with minimal costs (CXL, QY, JW, SZ).
ICML-2004-MaheUAPV #graph #kernel
Extensions of marginalized graph kernels (PM, NU, TA, JLP, JPV).
ICML-2004-MannorMHK #abstraction #clustering #learning
Dynamic abstraction in reinforcement learning via clustering (SM, IM, AH, UK).
ICML-2004-MannorSST #bias #estimation
Bias and variance in value function estimation (SM, DS, PS, JNT).
ICML-2004-MarlinZ #collaboration #multi
The multiple multiplicative factor model for collaborative filtering (BMM, RSZ).
ICML-2004-MelvilleM #learning
Diverse ensembles for active learning (PM, RJM).
ICML-2004-MerkeS #approximate #convergence #learning #linear
Convergence of synchronous reinforcement learning with linear function approximation (AM, RS).
ICML-2004-MoralesS #behaviour #learning
Learning to fly by combining reinforcement learning with behavioural cloning (EFM, CS).
ICML-2004-NatteeSNO #first-order #learning #mining #multi
Learning first-order rules from data with multiple parts: applications on mining chemical compound data (CN, SS, MN, TO).
ICML-2004-NguyenS #clustering #learning #using
Active learning using pre-clustering (HTN, AWMS).
ICML-2004-NguyenWJ #classification #detection #distributed #kernel #using
Decentralized detection and classification using kernel methods (XN, MJW, MIJ).
ICML-2004-OngMCS #kernel #learning
Learning with non-positive kernels (CSO, XM, SC, AJS).
ICML-2004-PeltonenSK #finite
Sequential information bottleneck for finite data (JP, JS, SK).
ICML-2004-PhillipsDS #approach #modelling
A maximum entropy approach to species distribution modeling (SJP, MD, RES).
ICML-2004-PieterN #learning
Apprenticeship learning via inverse reinforcement learning (PA, AYN).
ICML-2004-Potts #incremental #learning #linear
Incremental learning of linear model trees (DP).
ICML-2004-QiMPG #automation #predict
Predictive automatic relevance determination by expectation propagation (Y(Q, TPM, RWP, ZG).
ICML-2004-RayP #algorithm
Sequential skewing: an improved skewing algorithm (SR, DP).
ICML-2004-RosalesAF #clustering #learning #using
Learning to cluster using local neighborhood structure (RR, KA, BJF).
ICML-2004-RosencrantzGT #learning #predict
Learning low dimensional predictive representations (MR, GJG, ST).
ICML-2004-Rosset
Model selection via the AUC (SR).
ICML-2004-RuckertK #bound #learning #towards
Towards tight bounds for rule learning (UR, SK).
ICML-2004-RudarySP #adaptation #constraints #learning #reasoning
Adaptive cognitive orthotics: combining reinforcement learning and constraint-based temporal reasoning (MRR, SPS, MEP).
ICML-2004-Ryabko #learning #online
Online learning of conditionally I.I.D. data (DR).
ICML-2004-ScullyML
Coalition calculation in a dynamic agent environment (TS, MGM, GL).
ICML-2004-Shalev-ShwartzSN #learning #online #pseudo
Online and batch learning of pseudo-metrics (SSS, YS, AYN).
ICML-2004-SimsekB #abstraction #identification #learning #using
Using relative novelty to identify useful temporal abstractions in reinforcement learning (ÖS, AGB).
ICML-2004-SminchisescuJ #embedded #generative #modelling #visual notation
Generative modeling for continuous non-linearly embedded visual inference (CS, ADJ).
ICML-2004-Strens #performance #policy
Efficient hierarchical MCMC for policy search (MJAS).
ICML-2004-SuD #automation #component #probability
Automated hierarchical mixtures of probabilistic principal component analyzers (TS, JGD).
ICML-2004-SuttonRM #modelling #probability #random #sequence
Dynamic conditional random fields: factorized probabilistic models for labeling and segmenting sequence data (CAS, KR, AM).
ICML-2004-SzepesvariS
Interpolation-based Q-learning (CS, WDS).
ICML-2004-TaoSVO #approximate #learning #multi
SVM-based generalized multiple-instance learning via approximate box counting (QT, SDS, NVV, TTO).
ICML-2004-TaskarCK #learning #markov #network
Learning associative Markov networks (BT, VC, DK).
ICML-2004-ToutanovaMN #dependence #learning #modelling #random #word
Learning random walk models for inducing word dependency distributions (KT, CDM, AYN).
ICML-2004-TsochantaridisHJA #machine learning
Support vector machine learning for interdependent and structured output spaces (IT, TH, TJ, YA).
ICML-2004-VuralD #multi
A hierarchical method for multi-class support vector machines (VV, JGD).
ICML-2004-WeinbergerSS #kernel #learning #matrix #reduction
Learning a kernel matrix for nonlinear dimensionality reduction (KQW, FS, LKS).
ICML-2004-WellingRT #approximate #markov
Approximate inference by Markov chains on union spaces (MW, MRZ, YWT).
ICML-2004-WierstraW #markov #modelling
Utile distinction hidden Markov models (DW, MW).
ICML-2004-WingateS #named #parallel
P3VI: a partitioned, prioritized, parallel value iterator (DW, KDS).
ICML-2004-WuD #data flow
Improving SVM accuracy by training on auxiliary data sources (PW, TGD).
ICML-2004-XingSJ #process #type inference
Bayesian haplo-type inference via the dirichlet process (EPX, RS, MIJ).
ICML-2004-Ye #approximate #matrix #rank
Generalized low rank approximations of matrices (JY).
ICML-2004-YeJLP #analysis #feature model #linear
Feature extraction via generalized uncorrelated linear discriminant analysis (JY, RJ, QL, HP).
ICML-2004-Zadrozny #bias #classification #learning
Learning and evaluating classifiers under sample selection bias (BZ).
ICML-2004-Zhang #algorithm #linear #predict #probability #problem #scalability #using
Solving large scale linear prediction problems using stochastic gradient descent algorithms (TZ0).
ICML-2004-ZhangKY #algorithm
Surrogate maximization/minimization algorithms for AdaBoost and the logistic regression model (ZZ, JTK, DYY).
ICML-2004-ZhangY #estimation #probability
Probabilistic score estimation with piecewise logistic regression (JZ, YY).
ICML-2004-ZhangYK #algorithm #kernel #learning #matrix #using
Bayesian inference for transductive learning of kernel matrix using the Tanner-Wong data augmentation algorithm (ZZ, DYY, JTK).

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