ICML 2002 - PDF Preprint Papers

ICML 2002 Workshop on Statistical Network Analysis

Teaser Browsing | Click Here

Title Browsing | Click Here

Wall of Fame | Most Viewed ICML-2002 Paper

click to vote

ICML
2002
IEEE

241views Machine Learning» more ICML 2002»

Cranking: Combining Rankings Using Conditional Probability Models on Permutations

15 years 1 months ago

Download www.cc.gatech.edu

A new approach to ensemble learning is introduced that takes ranking rather than classification as fundamental, leading to models on the symmetric group and its cosets. The approa...

Guy Lebanon, John D. Lafferty

claim paper

Read More »

Disclaimer and Copyright Notice

Sciweavers respects the rights of all copyright holders and in this regard, authors are only allowed to share a link to their preprint paper on their own website. Every contribution is associated with a desciptive image. It is the sole responsibility of the authors to ensure that their posted image is not copyright infringing. This service is compliant with IEEE copyright.

Id	Views	Title	Status

1	241	Cranking: Combining Rankings Using Conditional Probability Models on Permutations	claim
2	218	An epsilon-Optimal Grid-Based Algorithm for Partially Observable Markov Decision Processes	claim
3	215	Combining Labeled and Unlabeled Data for MultiClass Text Categorization	claim
4	186	Is Combining Classifiers Better than Selecting the Best One	claim
5	183	Kernels for Semi-Structured Data	claim
6	174	Learning Decision Trees Using the Area Under the ROC Curve	claim
7	156	Algorithm-Directed Exploration for Model-Based Reinforcement Learning in Factored MDPs	claim
8	156	Active + Semi-supervised Learning = Robust Multi-View Learning	claim
9	155	Discovering Hierarchy in Reinforcement Learning with HEXQ	claim
10	149	Learning the Kernel Matrix with Semi-Definite Programming	claim
11	147	Exact model averaging with naive Bayesian classifiers	claim
12	146	On generalization bounds, projection profile, and margin distribution	claim
13	146	Hierarchically Optimal Average Reward Reinforcement Learning	claim
14	146	Learning to Share Distributed Probabilistic Beliefs	claim
15	145	Diffusion Kernels on Graphs and Other Discrete Input Spaces	claim
16	139	Multi-Instance Kernels	claim
17	138	Reinforcement Learning and Shaping: Encouraging Intended Behaviors	claim
18	138	Adaptive View Validation: A First Step Towards Automatic View Detection	claim
19	133	IEMS - The Intelligent Email Sorter	claim
20	133	Coordinated Reinforcement Learning	claim
21	131	Syllables and other String Kernel Extensions	claim
22	128	Pruning Improves Heuristic Search for Cost-Sensitive Learning	claim
23	127	Action Refinement in Reinforcement Learning by Probability Smoothing	claim
24	127	Learning word normalization using word suffix and context from unlabeled data	claim
25	122	An Alternate Objective Function for Markovian Fields	claim
26	118	Discriminative Feature Selection via Multiclass Variable Memory Markov Model	claim
27	115	Competitive Analysis of the Explore/Exploit Tradeoff	claim
28	114	Partially Supervised Classification of Text Documents	claim
29	113	Learning from Scarce Experience	claim
30	107	Learning Spatial and Temporal Correlation for Navigation in a 2-Dimensional Continuous World	claim
31	106	Exploiting Relations Among Concepts to Acquire Weakly Labeled Training Data	claim
32	106	Non-Disjoint Discretization for Naive-Bayes Classifiers	claim
33	104	A New Statistical Approach to Personal Name Extraction	claim
34	103	Interpreting and Extending Classical Agglomerative Clustering Algorithms using a Model-Based approach	claim
35	95	Univariate Polynomial Inference by Monte Carlo Message Length Approximation	claim
36	91	Linkage and Autocorrelation Cause Feature Selection Bias in Relational Learning	claim
37	86	Modeling Auction Price Uncertainty Using Boosting-based Conditional Density Estimation	claim
38	81	Randomized Variable Elimination	claim

Sciweavers

Explore & Download

Productivity Tools

Document Tools

Image Tools

Sciweavers