Proceedings of the 15th International Conference on Machine Learning
BibSLEIGH corpus
BibSLEIGH tags
BibSLEIGH bundles
BibSLEIGH people
EDIT!
CC-BY
Open Knowledge
XHTML 1.0 W3C Rec
CSS 2.1 W3C CanRec
email twitter

Jude W. Shavlik
Proceedings of the 15th International Conference on Machine Learning
ICML, 1998.

KER
DBLP
Scholar
Full names Links ISxN
@proceedings{ICML-1998,
	address       = "Madison, Wisconsin, USA",
	editor        = "Jude W. Shavlik",
	isbn          = "1-55860-556-8",
	publisher     = "{Morgan Kaufmann}",
	title         = "{Proceedings of the 15th International Conference on Machine Learning}",
	year          = 1998,
}

Contents (66 items)

ICML-1998-AbeM #learning #query #using
Query Learning Strategies Using Boosting and Bagging (NA, HM), pp. 1–9.
ICML-1998-AlerBI #approach #learning #multi #programming #search-based
Genetic Programming and Deductive-Inductive Learning: A Multi-Strategy Approach (RA, DB, PI), pp. 10–18.
ICML-1998-AnglanoGBS #concept #evaluation #learning
An Experimental Evaluation of Coevolutive Concept Learning (CA, AG, GLB, LS), pp. 19–27.
ICML-1998-BaxterTW #named
KnightCap: A Chess Programm That Learns by Combining TD(λ) with Game-Tree Search (JB, AT, LW), pp. 28–36.
ICML-1998-Bay #classification #multi #nearest neighbour #set
Combining Nearest Neighbor Classifiers Through Multiple Feature Subsets (SDB), pp. 37–45.
ICML-1998-BillsusP #collaboration #learning
Learning Collaborative Information Filters (DB, MJP), pp. 46–54.
ICML-1998-BlockeelRR #clustering #induction #top-down
Top-Down Induction of Clustering Trees (HB, LDR, JR), pp. 55–63.
ICML-1998-BollackerG #architecture #classification #reuse #scalability
A Supra-Classifier Architecture for Scalable Knowledge Reuse (KDB, JG), pp. 64–72.
ICML-1998-BonetG #learning #sorting
Learning Sorting and Decision Trees with POMDPs (BB, HG), pp. 73–81.
ICML-1998-BradleyM #feature model
Feature Selection via Concave Minimization and Support Vector Machines (PSB, OLM), pp. 82–90.
ICML-1998-BradleyF #clustering
Refining Initial Points for K-Means Clustering (PSB, UMF), pp. 91–99.
ICML-1998-Cesa-BianchiF #bound #finite #multi #problem
Finite-Time Regret Bounds for the Multiarmed Bandit Problem (NCB, PF), pp. 100–108.
ICML-1998-CristianiniSS #classification #scalability
Bayesian Classifiers Are Large Margin Hyperplanes in a Hilbert Space (NC, JST, PS), pp. 109–117.
ICML-1998-Dietterich #learning
The MAXQ Method for Hierarchical Reinforcement Learning (TGD), pp. 118–126.
ICML-1998-Domingos #heuristic
A Process-Oriented Heuristic for Model Selection (PMD), pp. 127–135.
ICML-1998-DzeroskiRB #learning #relational
Relational Reinforcement Learning (SD, LDR, HB), pp. 136–143.
ICML-1998-FrankW #generative #optimisation #set
Generating Accurate Rule Sets Without Global Optimization (EF, IHW), pp. 144–151.
ICML-1998-FrankW98a #mutation testing #permutation #using
Using a Permutation Test for Attribute Selection in Decision Trees (EF, IHW), pp. 152–160.
ICML-1998-Freitag #information management #learning #multi
Multistrategy Learning for Information Extraction (DF), pp. 161–169.
ICML-1998-FreundISS #algorithm #performance
An Efficient Boosting Algorithm for Combining Preferences (YF, RDI, RES, YS), pp. 170–178.
ICML-1998-FriedmanGL #classification #network #parametricity
Bayesian Network Classification with Continuous Attributes: Getting the Best of Both Discretization and Parametric Fitting (NF, MG, TJL), pp. 179–187.
ICML-1998-FriessCC #algorithm #kernel #learning #performance
The Kernel-Adatron Algorithm: A Fast and Simple Learning Procedure for Support Vector Machines (TTF, NC, CC), pp. 188–196.
ICML-1998-GaborKS #learning #multi
Multi-criteria Reinforcement Learning (ZG, ZK, CS), pp. 197–205.
ICML-1998-Gama
Local Cascade Generalization (JG), pp. 206–214.
ICML-1998-GarciaN #algorithm #analysis #learning
A Learning Rate Analysis of Reinforcement Learning Algorithms in Finite-Horizon (FG, SMN), pp. 215–223.
ICML-1998-Gordon
Well-Behaved Borgs, Bolos, and Berserkers (DFG), pp. 224–232.
ICML-1998-Heskes #approach #learning #multi
Solving a Huge Number of Similar Tasks: A Combination of Multi-Task Learning and a Hierarchical Bayesian Approach (TH), pp. 233–241.
ICML-1998-HuW #algorithm #framework #learning #multi
Multiagent Reinforcement Learning: Theoretical Framework and an Algorithm (JH, MPW), pp. 242–250.
ICML-1998-JuilleP #case study #learning
Coevolutionary Learning: A Case Study (HJ, JBP), pp. 251–259.
ICML-1998-KearnsS #learning
Near-Optimal Reinforcement Learning in Polynominal Time (MJK, SPS), pp. 260–268.
ICML-1998-KearnsM #algorithm #bottom-up #performance
A Fast, Bottom-Up Decision Tree Pruning Algorithm with Near-Optimal Generalization (MJK, YM), pp. 269–277.
ICML-1998-KimuraK #algorithm #analysis #learning #using
An Analysis of Actor/Critic Algorithms Using Eligibility Traces: Reinforcement Learning with Imperfect Value Function (HK, SK), pp. 278–286.
ICML-1998-KollerF #approximate #learning #probability #process #using
Using Learning for Approximation in Stochastic Processes (DK, RF), pp. 287–295.
ICML-1998-Lin #similarity
An Information-Theoretic Definition of Similarity (DL), pp. 296–304.
ICML-1998-LiquiereS #graph #machine learning
Structural Machine Learning with Galois Lattice and Graphs (ML, JS), pp. 305–313.
ICML-1998-LittmanJK #corpus #independence #learning #representation
Learning a Language-Independent Representation for Terms from a Partially Aligned Corpus (MLL, FJ, GAK), pp. 314–322.
ICML-1998-LochS #markov #policy #process #using
Using Eligibility Traces to Find the Best Memoryless Policy in Partially Observable Markov Decision Processes (JL, SPS), pp. 323–331.
ICML-1998-MargaritisT #3d #image #learning #sequence
Learning to Locate an Object in 3D Space from a Sequence of Camera Images (DM, ST), pp. 332–340.
ICML-1998-MaronR #classification #learning #multi
Multiple-Instance Learning for Natural Scene Classification (OM, ALR), pp. 341–349.
ICML-1998-McCallumN #classification #learning
Employing EM and Pool-Based Active Learning for Text Classification (AM, KN), pp. 350–358.
ICML-1998-McCallumRMN #classification
Improving Text Classification by Shrinkage in a Hierarchy of Classes (AM, RR, TMM, AYN), pp. 359–367.
ICML-1998-McCluskeyW #case study #requirements #using #validation
A Case Study in the Use of Theory Revision in Requirements Validation (TLM, MMW), pp. 368–376.
ICML-1998-MitaimK #adaptation #fuzzy #probability
Stochastic Resonance with Adaptive Fuzzy Systems (SM, BK), pp. 377–385.
ICML-1998-MooreSBL #learning #named #optimisation
Q2: Memory-Based Active Learning for Optimizing Noisy Continuous Functions (AWM, JGS, JAB, MSL), pp. 386–394.
ICML-1998-NakamuraA #algorithm #collaboration #predict #using
Collaborative Filtering Using Weighted Majority Prediction Algorithms (AN, NA), pp. 395–403.
ICML-1998-Ng #feature model #learning #on the
On Feature Selection: Learning with Exponentially Many Irrelevant Features as Training Examples (AYN), pp. 404–412.
ICML-1998-NockJ #on the #power of
On the Power of Decision Lists (RN, PJ), pp. 413–420.
ICML-1998-PendrithM #analysis #learning #markov
An Analysis of Direct Reinforcement Learning in Non-Markovian Domains (MDP, MM), pp. 421–429.
ICML-1998-PiaterCZA #performance #random
A Randomized ANOVA Procedure for Comparing Performance Curves (JHP, PRC, XZ, MA), pp. 430–438.
ICML-1998-PrecupU #approximate #classification #using
Classification Using Phi-Machines and Constructive Function Approximation (DP, PEU), pp. 439–444.
ICML-1998-ProvostFK #algorithm #estimation #induction
The Case against Accuracy Estimation for Comparing Induction Algorithms (FJP, TF, RK), pp. 445–453.
ICML-1998-RamachandranM #network #refinement
Theory Refinement of Bayesian Networks with Hidden Variables (SR, RJM), pp. 454–462.
ICML-1998-RandlovA #learning #using
Learning to Drive a Bicycle Using Reinforcement Learning and Shaping (JR, PA), pp. 463–471.
ICML-1998-ReddyT #first-order #learning #source code
Learning First-Order Acyclic Horn Programs from Entailment (CR, PT), pp. 472–480.
ICML-1998-RyanP #architecture #composition #learning #named
RL-TOPS: An Architecture for Modularity and Re-Use in Reinforcement Learning (MRKR, MDP), pp. 481–487.
ICML-1998-SalustowiczS #evolution #source code
Evolving Structured Programs with Hierarchical Instructions and Skip Nodes (RS, JS), pp. 488–496.
ICML-1998-SamuelCV #learning
An Investigation of Transformation-Based Learning in Discourse (KS, SC, KVS), pp. 497–505.
ICML-1998-Saul #automation #segmentation
Automatic Segmentation of Continuous Trajectories with Invariance to Nonlinear Warpings of Time (LKS), pp. 506–514.
ICML-1998-SaundersGV #algorithm #learning
Ridge Regression Learning Algorithm in Dual Variables (CS, AG, VV), pp. 515–521.
ICML-1998-SchneiderBM #scheduling
Value Function Based Production Scheduling (JGS, JAB, AWM), pp. 522–530.
ICML-1998-ShatkayK
Heading in the Right Direction (HS, LPK), pp. 531–539.
ICML-1998-Street #network #predict
A Neural Network Model for Prognostic Prediction (WNS), pp. 540–546.
ICML-1998-StuartB #learning
Learning the Grammar of Dance (JMS, EB), pp. 547–555.
ICML-1998-SuttonPS #learning
Intra-Option Learning about Temporally Abstract Actions (RSS, DP, SPS), pp. 556–564.
ICML-1998-TecuciK #education #student
Teaching an Agent to Test Students (GT, HK), pp. 565–573.
ICML-1998-WeissH #problem
The Problem with Noise and Small Disjuncts (GMW, HH), p. 574–?.

Bibliography of Software Language Engineering in Generated Hypertext (BibSLEIGH) is created and maintained by Dr. Vadim Zaytsev.
Hosted as a part of SLEBOK on GitHub.