24th Annual International Conference on Machine Learning (ICML), Corvallis 2007
43 Lectures · Jun 20, 2007
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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Uploaded videos:
Opening
Introduction to the ICML07 Conference
Jun 21, 2007
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8706 Views
Panel
ILP Invited Panel - Structured Machine Learning: The Next 10 Years
Jun 22, 2007
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9047 Views
Debate
Jul 27, 2007
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4590 Views
Introduction to the panel
Jul 27, 2007
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3236 Views
Ten problems for the next 10 years
Jul 27, 2007
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12513 Views
Declarative Vs. Procedural
Jul 27, 2007
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5632 Views
SRL - The next decade
Jul 27, 2007
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6620 Views
Reunited the splinter groups into one big relevanr force
Jul 27, 2007
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3447 Views
The next 10 years of ILP
Jul 27, 2007
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5445 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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27411 Views
Graphical Models for HIV Vaccine Design
Jun 22, 2007
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8155 Views
Metric Learning
Best Paper - Information-Theoretic Metric Learning
Jun 22, 2007
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17773 Views
Learning Distance Function by Coding Similarity
Jun 23, 2007
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6033 Views
A Transductive Framework of Distance Metric Learning by Spectral Dimensionality ...
Jun 23, 2007
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5995 Views
Dirichlet Aggregation: Unsupervised Learning towards an Optimal Metric for Propo...
Jun 23, 2007
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6070 Views
Relational Learning and ILR
Bias/variance analysis of relational domains
Jun 23, 2007
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8251 Views
Learning Probabilistic Stochastic Models from Probabilistic Examples
Jun 23, 2007
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6618 Views
Learning from Interpretations: A Rooted Kernel for Ordered Hypergraphs
Jun 23, 2007
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4633 Views
Statistical Predicate Invention
Jul 27, 2007
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6345 Views
Networks and Graphs
Scalable Modeling of Real Graphs using Kronecker Multiplication
Jun 23, 2007
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10071 Views
Recovering Temporally Rewiring Networks: A model-based approach
Jun 23, 2007
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5371 Views
Entire Regularization Paths for Graph Data
Oct 29, 2007
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3768 Views
Graph Clustering With Network Structure Indices
Jun 23, 2007
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8062 Views
Vision, Graphics and Robotics
Learning to Compress Images and Video
Jun 23, 2007
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8880 Views
Adaptive Mesh Compression in 3D Computer Graphics using Multiscale Manifold Lear...
Jun 23, 2007
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9043 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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7667 Views
Support Cluster Machine
Jun 23, 2007
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6810 Views
Trust Region Newton Methods for Large-Scale Logistic Regression
Jun 23, 2007
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9142 Views
Large-scale RLSC Learning Without Agony
Jun 23, 2007
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5296 Views
Language, Topic Modelling and Hierarchies
Unsupervised Prediction of Citation Influences
Jun 23, 2007
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7250 Views
Three New Graphical Models for Statistical Language Modelling
Jun 23, 2007
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7455 Views
Mixtures of Hierarchical Topics with Pachinko Allo cation
Jun 23, 2007
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9814 Views
Unsupervised Estimation for Noisy-Channel Models
Jun 23, 2007
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6038 Views
Hierarchical Maximum Entropy Density Estimation
Jun 23, 2007
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8349 Views
Metric Learning II
Learning for Efficient Retrieval of Structured Data with Noisy Queries
Jul 27, 2007
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3544 Views
Learning to Combine Distances for Complex Representations
Jun 23, 2007
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7120 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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10673 Views
Manifold-adaptive dimension estimation
Jun 24, 2007
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5145 Views
Adaptive Dimension Reduction Using Discriminant Analysis and K-means Clustering
Jul 27, 2007
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8353 Views
Robust Non-linear Dimensionality Reduction using Successive 1-Dimensional Laplac...
Jul 27, 2007
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7077 Views