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.
Visit the Conference website here.
Videos
Opening

Introduction to the ICML07 Conference
Jun 21, 2007
·
8710 views
Panel

ILP Invited Panel - Structured Machine Learning: The Next 10 Years
Jun 22, 2007
·
9051 views

The next 10 years of ILP
Jul 27, 2007
·
5449 views

Reunited the splinter groups into one big relevanr force
Jul 27, 2007
·
3451 views

SRL - The next decade
Jul 27, 2007
·
6624 views

Declarative Vs. Procedural
Jul 27, 2007
·
5636 views

Introduction to the panel
Jul 27, 2007
·
3239 views

Debate
Jul 27, 2007
·
4593 views

Ten problems for the next 10 years
Jul 27, 2007
·
12522 views
Invited talks

Graphical Models for HIV Vaccine Design
Jun 22, 2007
·
8162 views

Bayesian models of human inductive learning
Jun 22, 2007
·
27433 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
·
5997 views

Learning Distance Function by Coding Similarity
Jun 23, 2007
·
6038 views

Best Paper - Information-Theoretic Metric Learning
Jun 22, 2007
·
17781 views

Dirichlet Aggregation: Unsupervised Learning towards an Optimal Metric for Propo...
Jun 23, 2007
·
6073 views
Relational Learning and ILR

Statistical Predicate Invention
Jul 27, 2007
·
6355 views

Bias/variance analysis of relational domains
Jun 23, 2007
·
8253 views

Learning from Interpretations: A Rooted Kernel for Ordered Hypergraphs
Jun 23, 2007
·
4638 views

Learning Probabilistic Stochastic Models from Probabilistic Examples
Jun 23, 2007
·
6622 views
Networks and Graphs

Entire Regularization Paths for Graph Data
Oct 29, 2007
·
3770 views

Graph Clustering With Network Structure Indices
Jun 23, 2007
·
8068 views

Scalable Modeling of Real Graphs using Kronecker Multiplication
Jun 23, 2007
·
10080 views

Recovering Temporally Rewiring Networks: A model-based approach
Jun 23, 2007
·
5375 views
Vision, Graphics and Robotics

Map Building without Localization by Dimensionality Reduction Techniques
Jun 23, 2007
·
7005 views

Adaptive Mesh Compression in 3D Computer Graphics using Multiscale Manifold Lear...
Jun 23, 2007
·
9053 views

Learning to Compress Images and Video
Jun 23, 2007
·
8883 views
Large-scale Optimization

Support Cluster Machine
Jun 23, 2007
·
6814 views

Trust Region Newton Methods for Large-Scale Logistic Regression
Jun 23, 2007
·
9149 views

Scalable Training of L1-regularized Log-linear Models
Jun 23, 2007
·
7670 views

Large-scale RLSC Learning Without Agony
Jun 23, 2007
·
5307 views
Language, Topic Modelling and Hierarchies

Unsupervised Prediction of Citation Influences
Jun 23, 2007
·
7258 views

Unsupervised Estimation for Noisy-Channel Models
Jun 23, 2007
·
6042 views

Three New Graphical Models for Statistical Language Modelling
Jun 23, 2007
·
7463 views

Hierarchical Maximum Entropy Density Estimation
Jun 23, 2007
·
8353 views

Mixtures of Hierarchical Topics with Pachinko Allo cation
Jun 23, 2007
·
9823 views
Metric Learning II

Adaptive Dimension Reduction Using Discriminant Analysis and K-means Clustering
Jul 27, 2007
·
8357 views

Optimal Dimensionality of Metric Space for Classification
Jul 27, 2007
·
7266 views

Robust Non-linear Dimensionality Reduction using Successive 1-Dimensional Laplac...
Jul 27, 2007
·
7082 views

Manifold-adaptive dimension estimation
Jun 24, 2007
·
5148 views

Learning for Efficient Retrieval of Structured Data with Noisy Queries
Jul 27, 2007
·
3550 views

Non-Isometric Manifold Learning: Analysis and an Algorithm
Jun 23, 2007
·
10678 views

Learning to Combine Distances for Complex Representations
Jun 23, 2007
·
7124 views