Programme
TUESDAY, 14th of June
T Building (Computer Science), Aalto University School of Science, Konemiehentie 2, Espoo.
Workshops- 09.30-11.30: Computational intelligence for Quality of Life Environmental Information Services
Place: Hall T3 - 09.00-12.00: Validation of computational models in social and economic sciences
Place: Hall T4 - 10.00-16.30: Beyond correlations: Developments in supervised learning
algorithms for spiking neural networks
Place: Hall T2 - 13.00-17.00: Challenge workshop:
Mind reading competition on MEG data
Place: Hall T3 - 13.00-17.00: META-NET Workshop: Context in Machine Translation
Place: Hall T4
WEDNESDAY, 15th of June
Dipoli Congress Center, Otakaari 24, Espoo
08:45 Opening
(Hall 1)- Heikki Mannila, Vice-Rector of Aalto University
- Erkki Oja, Past President of ENNS
09:00 Plenary session
(Hall 1), chair: Alessandro Villa- Riitta Hari: Towards two-person neuroscience
10:00 Coffee
10:20 Generative Models
(Hall 1), chair: Thomas Martinetz- Jyri Kivinen and Christopher Williams:
Transformation Equivariant Boltzmann Machines - KyungHyun Cho, Alexander Ilin, and Tapani Raiko:
Improved Learning of Gaussian-Bernoulli Restricted Boltzmann Machines - David Reichert, Peggy Series, and Amos Storkey:
A Hierarchical Generative Model of Recurrent Object-Based Attention in the Visual Cortex
11:20 Brain-Computer Interfaces
(Hall 1), chair: Thomas Martinetz- Siamac Fazli, Marton Danoczy, Jürg Schelldorfer, and Klaus-Robert
Müller:
L1-penalized Linear Mixed-Effects Models for BCI - Sven Dähne, Johannes Höhne, Martijn Schreuder, and Michael
Tangermann:
Slow Feature Analysis - A Tool for Extraction of Discriminating Event-Related Potentials in Brain-Computer Interfaces
12:00 Lunch
13:00 Plenary session
(Hall 1), chair: Erkki Oja- Geoffrey Hinton: Learning structural descriptions of objects using equivariant capsules
14:00 Neural and Hybrid Architectures (Hall 1), chair: Stefan Wermter
- Jonathan Masci, Ueli Meier, Dan Ciresan, and Jürgen Schmidhuber:
Stacked Convolutional Auto-Encoders for Hierarchical Feature Extraction - Sander Bohte:
Error-backpropagation in Networks of Fractionally Predictive Spiking Neurons - Petia Koprinkova-Hristova and Guenther Palm:
ESN intrinsic plasticity versus reservoir stability - Snaider Carrillo, Jim Harkin, Liam McDaid, Sandeep Pande,
Seamus Cawley, and Fearghal Morgan:
Adaptive Routing Strategies for Large Scale Spiking Neural Network Hardware Implementations
14:00 Self-organization (Hall Luolamies), chair: Thomas Villmann
- Jan Faigl and Libor Preucil:
Self-Organizing Map for the Multi-Goal Path Planning with Polygonal Goals - Mathieu Lefort, Yann Boniface, and Bernard Girau:
Unlearning in the BCM learning rule for plastic self-organization in a multi-modal architecture - Matthew Cook, Florian Jug, and Christoph Krautz:
Neuronal Projections Can Be Sharpened by a Biologically Plausible Learning Mechanism - Ryotaro Kamimura:
Explicit Class Structure by Weighted Cooperative Learning
15:20 Coffee
15:50-17:00 Poster Spotlight Session (Hall 1), chair: Timo Honkela
- A series of walkthrough presentations without slides, about 1 minute for each spotlight
17:30-21:00 ICANN Reception and Poster Session (see the list below)
THURSDAY, 16th of June
Dipoli Congress Center, Otakaari 24, Espoo
09:00 Plenary session
(Hall 1), chair: Vera Kurkova (tbc)- Aapo Hyvärinen: Brain Imaging at rest: the ultimate neuroscience data set?
10:00 Coffee
10:20 Kernel Methods (Hall 1), chair: Alexander Ilin
- Hernan Ahumada, Guillermo Grinblat, and Pablo Granitto:
Unsupervized data-driven partitioning of multiclass problems - Giorgio Gnecco, Vera Kurkova, and Marcello Sanguineti:
Bounds for Approximate Solutions of Fredholm Integral Equations using Kernel Networks - Antti Airola, Tapio Pahikkala, and Tapio Salakoski:
An Improved Training Algorithm for the Linear Ranking Support Vector Machine - Fabio Aiolli, Giovanni Da San Martino, and Alessandro Sperduti:
Extending Tree Kernels with Topological Information - Frank-Michael Schleif, Andrej Gisbrecht, and Barbara Hammer:
Accelerating Kernel Neural Gas
10:20 Recurrent Networks and Temporal Processing (Hall Luolamies), chair: Jaakko Hollmen
- R. Felix Reinhart and Jochen Steil:
State Prediction: A Constructive Method to Program Recurrent Neural Networks - Yang Zhang, Shun Nishide, Toru Takahashi, Hiroshi Okuno, and
Tetsuya Ogata:
Cluster Self-organization of Known and Unknown Environmental Sounds using Recurrent Neural Network - Nikolay Nikolaev, Peter Tino, and Evgueni Smirnov:
Time-Dependent Series Variance Estimation via Recurrent Neural Networks - Hans-Georg Zimmermann, Alexey Minin, and Victoria Kusherbaeva:
Historical Consistent Complex Valued Recurrent Neural Network
12:00 Lunch
13:00 Plenary session
(Hall 1), chair: Samuel Kaski- John Shawe-Taylor: Leveraging the data generating distribution for learning
14:00 Bayesian Learning (Hall 1), chair: Stefanos Kollias
- Jouni Hartikainen, Jaakko Riihimäki, and Simo Särkkä:
Sparse Spatio-Temporal Gaussian Processes with General Likelihoods - Simo Särkkä:
Learning Curves for Gaussian Processes via Numerical Cubature Integration - Tommi Suvitaival, Ilkka Huopaniemi, Matej Oresic, and Samuel Kaski:
Cross-Species Translation of Multi-Way Biomarkers
14:00 Pattern recognition 1 (Hall Luolamies), chair: Günter Palm
- Masato Yonekawa and Hiroaki Kurokawa:
An Evaluation of the Image Recognition Method Using Pulse Coupled Neural Network - Enrique Romero:
Using the Leader Algorithm with Support Vector Machines for Large Data Sets - Borbala Hunyadi, Maarten De Vos, Marco Signoretto, Johan
Suykens, Wim Van Paesschen, and Sabine Van Huffel:
Automatic Seizure Detection Incorporating Structural Information
15:00 Coffee
15:30 Topic models and matrix factorization (Hall 1), chair: Amos Storkey
- Andrew Dai and Amos Storkey:
The Grouped Author-Topic Model for Unsupervised Entity Resolution - Zhirong Yang, He Zhang, Zhijian Yuan, and Erkki Oja:
Kullback-Leibler Divergence for Nonnegative Matrix Factorization
15:30 Dynamical Models (Hall Luolamies), chair: Alessandro Villa
- Yoshiyuki Asai and Alessandro Villa:
Distributed deterministic temporal information propagated by feedforward neural networks - Akio Yoshida and Yuko Osana:
Chaotic Complex-valued Multidirectional Associative Memory with Variable Scaling Factor
16:10-17:00 ENNS General Assembly (Hall 1)
18:30 Bus to Conference Dinner
Dipoli Congress Center, Otakaari 24, Espoo 09:00 Plenary session 10:00 Coffee 10:20 Cognitive Processes (Hall 1), chair: Risto Miikkulainen
10:20 Feature Extraction and Complex Networks (Hall Luolamies), chair: Tapani Raiko
12:00 Lunch 13:00 Plenary session 14:00 Panel Discussion (Hall 1)
15:00 Non-Linear Projection (Hall 1), chair: Amaury Lendasse
15:00 Pattern Recognition 2 (Hall Luolamies), chair: Olli Simula
16:00 Closing
FRIDAY, 17th of June
Predicting Reaction Times in Word Recognition by Unsupervised Learning of Morphology
An Examination of the Dynamic Interaction within Metaphor Understanding using a Model Simulation
Visual Pathways for Shape Abstraction
Improving Articulatory Feature and Phoneme Recognition using Multitask Learning
OrBEAGLE: Integrating Orthography into a Holographic Model of the Lexicon
On the Problem of Finding the Least Number of Features by L1-Norm Minimisation
Extracting Coactivated Features from Multiple Data Sets
Single Layer Complex Valued Neural Network with Entropic Cost Function
Batch Intrinsic Plasticity for Extreme Learning Machines
An Empirical Study on the Performance of Spectral Manifold Learning Techniques
Semi-supervised Learning for WLAN Positioning
Ensemble-Teacher Learning through a Perceptron Rule with a Margin
Topic-dependent Document Ranking: Citation Network Analysis by Analogy to Memory Retrieval in the Brain
PADDLE: Proximal Algorithm for Dual Dictionaries LEarning
POSTERS
A Markov Random Field Approach to Neural Encoding and Decoding
Weakly Supervised Learning of Foreground-Background Segmentation using Masked RBMs
Recursive Multi-Way PLS for Adaptive Calibration of Brain Computer Interface System
Transformation of Edge Weights in a Graph Bipartitioning Problem
A Distributed Behavioral Model using Neural Fields
A Hypothetical Free Synaptic Energy Function and Related States of Synchrony
Observational Learning Based on Models of Overlapping Pathways
On the Capacity of Transient Internal States in Liquid-State Machines
Hybrid Parallel Classifiers for Semantic Subspace Learning
Temperature Prediction in Electric Arc Furnace with Neural Network Tree
Optimizing Linear Discriminant Error Correcting Output Codes Using Particle Swarm Optimization
SOS-HMM - Self-Organizing Structure of Hidden Markov Model
Image Receptive Fields Neural Networks for Object Recognition
A Comparison of the Electric Potential through the Membranes of Ganglion Neurons and Neuroblastoma Cells
SNPboost: Interaction Analysis and Risk Prediction on GWA Data
Binary Patterns Identification by Vector Neural Network with Measure of Proximity Between Neuron States
Emerging Bayesian Priors in a Self-Organizing Recurrent Network
Momentum Acceleration of Least-Squares Support Vector Machines
Fast Support Vector Training by Newton's Method
Linear Operators and Stochastic Partial Differential Equations in Gaussian Process Regression
Learning from Multiple Annotators with Gaussian Processes
Estimation of the Number of Clusters Using Heterogeneous Multiple Classifier System
A Distributed Self-adaptive Nonparametric Change-Detection Test for Sensor/Actuator Networks
Weighted Mutual Information for Feature Selection
Face Prediction from fMRI Data During Movie Stimulus Strategies for Feature Selection
The Authentication System for Multi-Modal Behavior Biometrics using Concurrent Pareto Learning SOM
Hermite Polynomials and Measures of Non-Gaussianity
Complex-Valued Independent Component Analysis of Natural Images
Improving Gaussian Process Value Function Approximation in Policy Gradient Algorithms
Application of Nonlinear Neural Network Model for Self Sensing Characteristic in an Ionic Polymer Metal Composite (IPMC) Actuator
Optimal Control Using Functional Type SIRMs Fuzzy Reasoning Method
High-Dimensional Surveillance
A One-layer Dual Recurrent Neural Network with a Heaviside Step Activation Function for Linear Programming with Its Linear Assignment Application
Neural Network Solution of Optimal Control Problem with Control and State Constraints
Singular Perturbation Approach with Matsuoka Oscillator and Synchronization Phenomena
A RANSAC-based ISOMAP for Filiform Manifolds in Nonlinear Dynamical Systems
Manifold Learning for Visualization of Vibrational States of a Rotating Machine
Bias of Importance Measures for Multi-valued Attributes and Solutions
A Computationally Efficient Information Estimator for Weighted Data
Top-down Induction of Reduced Ordered Decision Diagrams from Neural Networks
A Framework for Application-Oriented Design of Large-Scale Neural Networks
A Dynamic Field Model of Ordinal and Timing Properties of Sequential Events
Robot Trajectory Prediction and Recognition based on a Computational Mirror Neurons Model
A Sentence Generation Network that Learns Surface and Abstract Syntactic Structures
A Perceptual Memory System for Affordance Learning in Humanoid Robots
Probabilistic Proactive Timeline Browser
Person Tracking based on a Hybrid Neural Probabilistic Model
Gaze- and Speech-Enhanced Content-Based Image Retrieval in Image Tagging
Modelling Hypothetical Wage Equation by Neural Networks
On the Designing of Spikes Band-Pass Filters for FPGA
An Information Geometrical View of Stationary Subspace Analysis
Forecasting Road Condition after Maintenance Works by Linear Methods and Radial Basis Function Networks
Multistart Strategy using Delta Test for Variable Selection
Speech Recognition Based on the Processing Solutions of Auditory Cortex
A Geometric Bio-Inspired Model for Recognition of Low-Level Structures
View-tuned Approximate Partial Matching Kernel from Hierarchical Growing Neural Gases
ANGE - Automatic Neural Generator
Uncertainty Sampling-Based Active Selection of Datasetoids for Meta-Learning
Learning Scheme for Complex Neural Networks Using Simultaneous Perturbation