About
The 24th Annual International Conference on Machine Learning was held in conjunction with the 2007 International Conference on Inductive Logic Programming at Oregon State University in Corvallis, Oregon. As a broad subfield of artificial intelligence, machine learning is concerned with the design and development of algorithms and techniques that allow computers to "learn". At a general level, there are two types of learning: inductive, and deductive.
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Related categories
Uploaded videos:
Opening
Introduction to the ICML07 Conference
Jun 21, 2007
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8705 Views
Panel
The next 10 years of ILP
Jul 27, 2007
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5445 Views
Reunited the splinter groups into one big relevanr force
Jul 27, 2007
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3440 Views
SRL - The next decade
Jul 27, 2007
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6619 Views
Declarative Vs. Procedural
Jul 27, 2007
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5629 Views
ILP Invited Panel - Structured Machine Learning: The Next 10 Years
Jun 22, 2007
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9040 Views
Ten problems for the next 10 years
Jul 27, 2007
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12512 Views
Debate
Jul 27, 2007
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4589 Views
Introduction to the panel
Jul 27, 2007
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3234 Views
Invited talks
Kernel Tricks, Means and Ends
Jun 21, 2007
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15231 Views
Bayesian models of human inductive learning
Jun 22, 2007
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27406 Views
Graphical Models for HIV Vaccine Design
Jun 22, 2007
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8152 Views
Metric Learning
Best Paper - Information-Theoretic Metric Learning
Jun 22, 2007
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17770 Views
Learning Distance Function by Coding Similarity
Jun 23, 2007
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6032 Views
A Transductive Framework of Distance Metric Learning by Spectral Dimensionality ...
Jun 23, 2007
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5993 Views
Dirichlet Aggregation: Unsupervised Learning towards an Optimal Metric for Propo...
Jun 23, 2007
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6064 Views
Relational Learning and ILR
Bias/variance analysis of relational domains
Jun 23, 2007
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8249 Views
Learning Probabilistic Stochastic Models from Probabilistic Examples
Jun 23, 2007
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6616 Views
Learning from Interpretations: A Rooted Kernel for Ordered Hypergraphs
Jun 23, 2007
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4632 Views
Statistical Predicate Invention
Jul 27, 2007
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6341 Views
Networks and Graphs
Scalable Modeling of Real Graphs using Kronecker Multiplication
Jun 23, 2007
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10068 Views
Recovering Temporally Rewiring Networks: A model-based approach
Jun 23, 2007
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5368 Views
Entire Regularization Paths for Graph Data
Oct 29, 2007
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3767 Views
Graph Clustering With Network Structure Indices
Jun 23, 2007
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8061 Views
Vision, Graphics and Robotics
Learning to Compress Images and Video
Jun 23, 2007
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8876 Views
Adaptive Mesh Compression in 3D Computer Graphics using Multiscale Manifold Lear...
Jun 23, 2007
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9039 Views
Map Building without Localization by Dimensionality Reduction Techniques
Jun 23, 2007
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7002 Views
Large-scale Optimization
Scalable Training of L1-regularized Log-linear Models
Jun 23, 2007
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7664 Views
Support Cluster Machine
Jun 23, 2007
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6808 Views
Trust Region Newton Methods for Large-Scale Logistic Regression
Jun 23, 2007
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9141 Views
Large-scale RLSC Learning Without Agony
Jun 23, 2007
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5294 Views
Language, Topic Modelling and Hierarchies
Unsupervised Prediction of Citation Influences
Jun 23, 2007
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7246 Views
Three New Graphical Models for Statistical Language Modelling
Jun 23, 2007
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7452 Views
Mixtures of Hierarchical Topics with Pachinko Allo cation
Jun 23, 2007
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9811 Views
Unsupervised Estimation for Noisy-Channel Models
Jun 23, 2007
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6036 Views
Hierarchical Maximum Entropy Density Estimation
Jun 23, 2007
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8347 Views
Metric Learning II
Learning for Efficient Retrieval of Structured Data with Noisy Queries
Jul 27, 2007
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3539 Views
Learning to Combine Distances for Complex Representations
Jun 23, 2007
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7119 Views
Optimal Dimensionality of Metric Space for Classification
Jul 27, 2007
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7261 Views
Non-Isometric Manifold Learning: Analysis and an Algorithm
Jun 23, 2007
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10671 Views
Manifold-adaptive dimension estimation
Jun 24, 2007
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5141 Views
Adaptive Dimension Reduction Using Discriminant Analysis and K-means Clustering
Jul 27, 2007
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8351 Views
Robust Non-linear Dimensionality Reduction using Successive 1-Dimensional Laplac...
Jul 27, 2007
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7075 Views