Neural Information Processing Systems Conference and Workshops
December 5-10, 2013
Lake Tahoe, Nevada, USA
Deadline for Paper Submissions: Friday, May 31, 2013, 11 pm Universal Time (4
pm Pacific Daylight Time). Submit at:
Submissions are solicited for the Twenty-Seventh Annual Conference on Neural
Information Processing Systems, 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 2013
conference will be held on December 5-8 at Lake Tahoe, Nevada. One day of
tutorials (December 5) will precede the main conference, and two days of
workshops (December 9-10) will follow it at the same location. Note that
differently from previous years, the conference will start on a Thursday.
Submission process: Electronic submissions will be accepted until Friday, May
31, 2013, 11 pm Universal Time (4 pm Pacific Daylight Time). As was the case
last year, final papers will be due in advance of the conference. However,
minor changes such as typos and additional references will still be allowed
for a certain period after the conference.
Reviewing: As in previous years, reviewing will be double-blind: the
reviewers will not know the identities of the authors. However, differently
from previous years, anonymous reviews and meta-reviews of accepted papers
will be made public after the end of the review process.
Evaluation Criteria: Submissions will be refereed on the basis of technical
quality, novelty, potential impact, and clarity.
Dual Submissions Policy: Submissions that are identical (or substantially
similar) to versions that have been previously published, or accepted for
publication, or that have been submitted in parallel to other conferences are
not appropriate for NIPS and violate our dual submission policy. Exceptions
to this rule are the following:
1. Submission is permitted of a short version of a paper that has been
submitted to a journal, but has not yet been published in that journal.
Authors must declare such dual-submissions either through the CMT submission
form, or via email to the program chairs at [log in to unmask] It is the
authors’ responsibility to make sure that the journal in question allows dual
concurrent submissions to conferences.
2. Submission is permitted for papers presented or to be presented at
conferences or workshops without proceedings, or with only abstracts
Previously published papers with substantial overlap written by the authors
must be cited so as to preserve author anonymity (e.g. “the authors of 
prove that …”). Differences relative to these earlier papers must be
explained in the text of the submission.
It is acceptable to submit to NIPS 2013 work that has been made available as
a technical report (or similar, e.g. in arXiv) without citing it. While this
could compromise the authors' anonymity, reviewers will be asked to refrain
from actively searching for the authors’ identity or disclose to the area
chairs if their identity is known to them.
The dual-submission rules apply during the NIPS review period which begins
May 31 and ends September 5, 2013.
Submission Instructions: All submissions will be made electronically, in PDF
format. Papers are limited to eight pages, including figures and tables, in
the NIPS style. An additional ninth page containing only cited references is
allowed. Complete submission and formatting instructions, including style
files, are available from the NIPS website, http://nips.cc.
Supplementary Material: Authors can submit up to 10 MB of material,
containing proofs, audio, images, video, data or source code. Note that the
reviewers and the program committee reserve the right to judge the paper
solely on the basis of the 9 pages of the paper; looking at any extra
material is up to the discretion of the reviewers and is not required.
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
* 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,
* 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,
* 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
* 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.
Demonstrations and Workshops: There is a separate Demonstration track at
NIPS. Authors wishing to submit to the Demonstration track should consult the
Call for Demonstrations.
The workshops will be held at Lake Tahoe, Nevada, December 9-10. The upcoming
call for workshop proposals will provide details.
Web URL: https://nips.cc/Conferences/2013/CallForPapers