NIPS 2014

Events

  • 08 December - 11 December 2014
  • Montreal, Canada
  • Organiser: Neural Imaging Processing Systems Foundation
  • Event Details

The Twenty-Eigth Annual Conference on Neural Information Processing Systems is an interdisciplinary conference that brings together researchers in all aspects of neural and statistical information processing and computation, and their applications.

The conference is a highly selective, single track meeting that includes oral and poster presentations of refereed papers as well as invited talks. The 2014 conference will be held on December 8-11 at Montreal Convention Center, Montreal, Canada. One day of tutorials (December 8) will precede the main conference, and two days of workshops (December 12-13) will follow it at the same location.

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, Bayesian methods, neural networks, deep learning, dimensionality reduction and manifold learning, model selection, combinatorial optimization, relational and structured learning.


•Applications: innovative applications 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.

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