CLASS-L Archives

May 2013

CLASS-L@LISTS.SUNYSB.EDU

Options: Use Proportional Font
Show Text Part by Default
Condense Mail Headers

Message: [<< First] [< Prev] [Next >] [Last >>]
Topic: [<< First] [< Prev] [Next >] [Last >>]
Author: [<< First] [< Prev] [Next >] [Last >>]

Print Reply
Mime-Version:
1.0
Content-Type:
text/plain; charset="ISO-8859-1"
Date:
Sun, 5 May 2013 09:22:32 -0400
Reply-To:
"Classification, clustering, and phylogeny estimation" <[log in to unmask]>
Subject:
Content-Transfer-Encoding:
quoted-printable
Message-ID:
Sender:
"Classification, clustering, and phylogeny estimation" <[log in to unmask]>
From:
Chris Hiestand <[log in to unmask]>
Parts/Attachments:
text/plain (130 lines)
Neural Information Processing Systems Conference and Workshops
December 5-10, 2013 
Lake Tahoe, Nevada, USA

http://nips.cc/Conferences/2013/

Deadline for Paper Submissions: Friday, May 31, 2013, 11 pm Universal Time (4 
pm Pacific Daylight Time). Submit at: 
https://cmt.research.microsoft.com/NIPS2013/

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 
published.

Previously published papers with substantial overlap written by the authors 
must be cited so as to preserve author anonymity (e.g. “the authors of [1] 
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 
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.

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

----------------------------------------------
CLASS-L list.
Instructions: http://www.classification-society.org/csna/lists.html#class-l

ATOM RSS1 RSS2