PROGRAM


Sunday September 23, 2012
14:00-19:30Registration
15:00-17:00Tutorial: Privacy-Preserving Speech and Audio Processing

Prof. Bhiksha Raj
Carnegie Mellon University, USA

17:00-17:30Coffee Break
17:30-19:30Tutorial: Manifold Learning: Modeling and Algorithms

Prof. Raviv Raich
Oregon State University, USA

20:30-21:30Welcome Reception at Palacio Magdalena


Monday September 24, 2012
8:30-19:30Registration
9:15-9:30Opening Session
9:30-10:30Plenary Lecture: Learning and Message-Passing in Graphical Models

Prof. Martin J. Wainwright
Statistics and EECS, UC Berkeley, USA

10:30-11:00Coffee Break
11:00-13:00
Oral Session 1: Pattern Recognition and Classification
Chair: Jan Larsen, DTU Informatics, Denmark

11:00
Facial Expression Recognition With Robust Covariance Estimation And Support Vector Machines
Nicholas Vretos, Anastasios Tefas, Ioannis Pitas
11:20
Local Distance Metric Learning For Efficient Conformal Predictors
Michael Pekala, Ashley Llorens, I-Jeng Wang
11:40
Simultaneous And Proportional Control Of 2D Wrist Movements With Myoelectric Signals
Janne Mathias Hahne, Hubertus Rehbaum, Felix Biessmann, Frank C. Meinecke, Klaus-Robert Müller , Ning Jiang, Dario Farina, Lucas C. Parra
12:00
Landmine Detection With Multiple Instance Hidden Markov Models
Seniha Esen Yuksel, Jeremy Bolton, Paul Gader
12:20
Handling Missing Features In Maximum Margin Bayesian Network Classifiers
Sebastian Tschiatschek, Nikolaus Mutsam, Franz Pernkopf
12:40
Classifier-Based Affinities For Clustering Sets Of Vectors
Darío García-García, Raúl Santos-Rodríguez, Emilio Parrado-Hernández
13:00-15:00Lunch
15:00-17:00
Poster Session 1
Chair: Emilio Parrado-Hernández, Universidad Carlos III de Madrid, Spain

17:00-17:30Coffee Break
17:30-19:30
Poster Session 2
Chair: Weifeng Liu, Amazon.com, USA


Tuesday September 25, 2012
9:00-19:30Registration
9:30-10:30Plenary Lecture: Large-scale convex optimization for machine learning

PASCAL invited speaker Dr. Francis Bach
INRIA, France

10:30-11:00Coffee Break
11:00-13:00
Oral Session 2: Bayesian Learning
Chair: Fernando Pérez-Cruz, Universidad Carlos III de Madrid, Spain

11:00
Distributed Variational Sparse Bayesian Learning For Sensor Networks
Thomas Buchgraber, Dmitriy Shutin
11:20
Trading Approximation Quality Versus Sparsity Within Incremental Automatic Relevance Determination Frameworks
Dmitriy Shutin, Thomas Buchgraber
11:40
Estimation Of The Forgetting Factor In Kernel Recursive Least Squares
Steven Van Vaerenbergh, Ignacio Santamaria, Miguel Lazaro-Gredilla
12:00
Latent Dirichlet Learning For Hierarchical Segmentation
Jen-Tzung Chien, Chuang-Hua Chueh
12:20
Identifying Modular Relations In Complex Brain Networks
Kasper Winther Andersen, Morten Mørup, Hartwig Siebner, Kristoffer H Madsen, Lars Kai Hansen
12:40
Probabilistic Interpolative Decomposition
Ismail Ari, A. Taylan Cemgil, Lale Akarun
13:00-15:00Lunch (TC meeting)
15:00-17:00
Oral Session 3: Special Session on Social Network Analysis & Data Competition
Chair: Morten Mørup, DTU Informatics, Denmark

15:00
Quantifying Spatiotemporal Dynamics Of Twitter Replies To News Feeds
Felix Bießmann, Jens-Michalis Papaioannou, Andreas Harth, Matthias L. Jugel, Klaus-Robert Müller, Mikio Braun
15:20
Link Prediction In Weighted Networks
David Kofoed Wind, Morten Mørup
15:40
A Random Walk Based Model Incorporating Social Information For Recommendations
Shang Shang, Sanjeev R. Kulkarni, Paul W. Cuff, Pan Hui
16:00
Iterative Collaborative Filtering For Recommender Systems With Sparse Data
Zhuo Zhang, Paul Cuff, Sanjeev Kulkarni
16:20
Opportunistic Sensing: Unattended Acoustic Sensor Selection Using Crowdsourcing Models
Po-Sen Huang, Mark Hasegawa-Johnson, Wotao Yin, Thomas S. Huang
16:40
The Eight Annual MLSP Competition: Overview
Ken Montanez, Weifeng Liu, Vince D. Calhoun, Catherine Huang, Kenneth E. Hild Ii
17:00-17:30Coffee Break
17:30-19:30
Poster Session 3
Chair: Javier Vía, Universidad de Cantabria, Spain

21:00-23:00Banquet at Casino Santander


Wednesday September 26, 2012
9:00-13:00Registration
9:30-10:30Plenary Lecture: Adaptation and Learning over Complex Networks

Prof. Ali H. Sayed
UCLA Electrical Engineering, USA

10:30-11:00Coffee Break
11:00-13:00
Oral Session 4: Learning Theory and Algorithms
Chair: David J. Miller, The Pennsylvania State University, USA

11:00
Mixture Weight Influence On Kernel Entropy Component Analysis And Semi-Supervised Learning Using The Lasso
Jonas N. Myhre, Robert Jenssen
11:20
On Surrogate Supervision Multiview Learning
Gaole Jin, Raviv Raich
11:40
On The Generalization Ability Of Distributed Online Learners
Zaid J. Towfic, Jianshu Chen, Ali H. Sayed
12:00
A Novel Scheme For Diffusion Networks With Least-Squares Adaptive Combiners
Jesús Fernández-Bes, Luiz A. Azpicueta-Ruiz, Magno T. M. Silva, Jerónimo Arenas-García
12:20
Unsupervised Feature Selection Based On Non-Parametric Mutual Information
Lev Faivishevsky, Jacob Goldberger
12:40
Stochastic Unfolding
Ke Sun, Eric Bruno, Stéphane Marchand-Maillet
13:00-17:00Boat trip, lunch in Pedreña and good bye