Jun 20, 2007 
43 videos 
24th Annual International Conference on Machine Learning (ICML), Corvallis 2007
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.
Visit the Conference website here.
Opening
Introduction to the ICML07 Conference
Jun 21, 2007 8731 views
Panel
ILP Invited Panel - Structured Machine Learning: The Next 10 Years
Jun 22, 2007 9068 views
The next 10 years of ILP
Jul 27, 2007 5471 views
Reunited the splinter groups into one big relevanr force
Jul 27, 2007 3470 views
SRL - The next decade
Jul 27, 2007 6642 views
Declarative Vs. Procedural
Jul 27, 2007 5674 views
Introduction to the panel
Jul 27, 2007 3270 views
Debate
Jul 27, 2007 4611 views
Ten problems for the next 10 years
Jul 27, 2007 12565 views
Invited talks
Graphical Models for HIV Vaccine Design
Jun 22, 2007 8197 views
Bayesian models of human inductive learning
Jun 22, 2007 27524 views
Kernel Tricks, Means and Ends
Jun 21, 2007 15231 views
Metric Learning
A Transductive Framework of Distance Metric Learning by Spectral Dimensionality ...
Jun 23, 2007 6022 views
Learning Distance Function by Coding Similarity
Jun 23, 2007 6058 views
Best Paper - Information-Theoretic Metric Learning
Jun 22, 2007 17819 views
Dirichlet Aggregation: Unsupervised Learning towards an Optimal Metric for Propo...
Jun 23, 2007 6099 views
Relational Learning and ILR
Statistical Predicate Invention
Jul 27, 2007 6387 views
Bias/variance analysis of relational domains
Jun 23, 2007 8273 views
Learning from Interpretations: A Rooted Kernel for Ordered Hypergraphs
Jun 23, 2007 4666 views
Learning Probabilistic Stochastic Models from Probabilistic Examples
Jun 23, 2007 6637 views
Networks and Graphs
Entire Regularization Paths for Graph Data
Oct 29, 2007 3791 views
Graph Clustering With Network Structure Indices
Jun 23, 2007 8093 views
Scalable Modeling of Real Graphs using Kronecker Multiplication
Jun 23, 2007 10160 views
Recovering Temporally Rewiring Networks: A model-based approach
Jun 23, 2007 5400 views
Vision, Graphics and Robotics
Map Building without Localization by Dimensionality Reduction Techniques
Jun 23, 2007 7033 views
Adaptive Mesh Compression in 3D Computer Graphics using Multiscale Manifold Lear...
Jun 23, 2007 9087 views
Learning to Compress Images and Video
Jun 23, 2007 8915 views
Large-scale Optimization
Support Cluster Machine
Jun 23, 2007 6832 views
Trust Region Newton Methods for Large-Scale Logistic Regression
Jun 23, 2007 9171 views
Scalable Training of L1-regularized Log-linear Models
Jun 23, 2007 7695 views
Large-scale RLSC Learning Without Agony
Jun 23, 2007 5331 views
Language, Topic Modelling and Hierarchies
Unsupervised Prediction of Citation Influences
Jun 23, 2007 7293 views
Unsupervised Estimation for Noisy-Channel Models
Jun 23, 2007 6061 views
Three New Graphical Models for Statistical Language Modelling
Jun 23, 2007 7491 views
Hierarchical Maximum Entropy Density Estimation
Jun 23, 2007 8369 views
Mixtures of Hierarchical Topics with Pachinko Allo cation
Jun 23, 2007 9870 views
Metric Learning II
Adaptive Dimension Reduction Using Discriminant Analysis and K-means Clustering
Jul 27, 2007 8381 views
Optimal Dimensionality of Metric Space for Classification
Jul 27, 2007 7299 views
Robust Non-linear Dimensionality Reduction using Successive 1-Dimensional Laplac...
Jul 27, 2007 7101 views
Manifold-adaptive dimension estimation
Jun 24, 2007 5173 views
Learning for Efficient Retrieval of Structured Data with Noisy Queries
Jul 27, 2007 3568 views
Non-Isometric Manifold Learning: Analysis and an Algorithm
Jun 23, 2007 10712 views
Learning to Combine Distances for Complex Representations
Jun 23, 2007 7143 views