NIPS 2011 - Twenty-fifth Annual Conference on Neural Information Processing Systems NIPS 2011

NIPS 2011
Tutorials ? December 12, 2011
Granada Congress and Exhibition Centre, Granada, Spain
Conference Sessions ? December 13-15, 2011
Granada Congress and Exhibition Centre, Grenada, Spain
Workshops ? December 16-17, 2011
Melia Sierra Nevada & Melia Sol y Nieve, Sierra Nevada, Spain

Technical Areas: Papers are solicited in all areas of neural information processing and statistical learning, including, but not limited to:

Algorithms and Architectures: statistical learning algorithms, kernel methods, graphical models, Gaussian processes, neural networks, dimensionality reduction and manifold learning, model selection, combinatorial optimization, relational and structured learning.
Applications: innovative applications or fielded systems that use machine learning, including systems for time series prediction, bioinformatics, systems biology, text/web analysis, multimedia processing, and robotics.
Brain Imaging: neuroimaging, cognitive neuroscience, EEG (electroencephalogram), ERP (event related potentials), MEG (magnetoencephalogram), fMRI (functional magnetic resonance imaging), brain mapping, brain segmentation, brain computer interfaces.
Cognitive Science and Artificial Intelligence: theoretical, computational, or experimental studies of perception, psychophysics, human or animal learning, memory, reasoning, problem solving, natural language processing, and neuropsychology.
Control and Reinforcement Learning: decision and control, exploration, planning, navigation, Markov decision processes, game playing, multi-agent coordination, computational models of classical and operant conditioning.
Hardware Technologies: analog and digital VLSI, neuromorphic engineering, computational sensors and actuators, microrobotics, bioMEMS, neural prostheses, photonics, molecular and quantum computing.
Learning Theory: generalization, regularization and model selection, Bayesian learning, spaces of functions and kernels, statistical physics of learning, online learning and competitive analysis, hardness of learning and approximations, statistical theory, large deviations and asymptotic analysis, information theory.
Neuroscience: theoretical and experimental studies of processing and transmission of information in biological neurons and networks, including spike train generation, synaptic modulation, plasticity and adaptation.
Speech and Signal Processing: recognition, coding, synthesis, denoising, segmentation, source separation, auditory perception, psychoacoustics, dynamical systems, recurrent networks, language models, dynamic and temporal models.
Visual Processing: biological and machine vision, image processing and coding, segmentation, object detection and recognition, motion detection and tracking, visual psychophysics, visual scene analysis and interpretation.