COLT 2017

COLT 2017
30th Annual Conference on Learning Theory
Event in series	COLT
Dates	2017/07/07 (iCal) - 2017/10/07
Homepage:	http://www.learningtheory.org/colt2017/
Location
Location:	Amsterdam, Netherlands
Loading map... {"minzoom":false,"maxzoom":false,"mappingservice":"leaflet","width":"280px","height":"280px","centre":false,"title":"","label":"","icon":"","visitedicon":"","lines":[],"polygons":[],"circles":[],"rectangles":[],"wmsoverlay":false,"copycoords":false,"static":false,"zoom":false,"defzoom":14,"layers":["OpenStreetMap"],"overlaylayers":[],"resizable":false,"enablefullscreen":false,"scrollwheelzoom":true,"markercluster":false,"clustermaxzoom":20,"clusterzoomonclick":true,"clustermaxradius":80,"clusterspiderfy":true,"geojson":"","locations":[{"text":"\u003Cb\u003E\u003Cdiv class=\"mw-parser-output\"\u003E\u003C/div\u003E\u003C/b\u003E\u003Chr /\u003E\u003Cdiv class=\"mw-parser-output\"\u003E\u003C/div\u003E","title":"","link":"","lat":52.3730796,"lon":4.8924534,"icon":""}],"imageoverlays":null}
Early bird student:	€ 150 / {{{Early bird fee reduced}}} Property "Early bird fee reduced" (as page type) with input value "{{{Early bird fee reduced}}}" contains invalid characters or is incomplete and therefore can cause unexpected results during a query or annotation process. (reduced)
On site student:	€ 350 / {{{On site fee reduced}}} Property "On site fee reduced" (as page type) with input value "{{{On site fee reduced}}}" contains invalid characters or is incomplete and therefore can cause unexpected results during a query or annotation process. (reduced)
Early bird regular:	€ 250
On site regular:	€ 600
Papers:	Submitted 228 / Accepted 73 (32 %)
Table of Contents

The 30th Annual Conference on Learning Theory (COLT 2017) will take place in Amsterdam, the Netherlands, on July 7-10, 2017

Topics

Design and analysis of learning algorithms Statistical and computational complexity of learning Optimization models and algorithms for learning Unsupervised, semi-supervised, and active learning Online learning Artificial neural networks, including deep learning Learning with large-scale datasets Decision making under uncertainty Bayesian methods in learning High dimensional and non-parametric statistical inference Planning and control, including reinforcement learning Learning with additional constraints: e.g. privacy, memory or communication budget Learning in other settings: e.g. social, economic, and game-theoretic Analysis and applications of learning theory in related fields: natural language processing, neuroscience, bioinformatics, privacy and security, machine vision, information retrieval

Important Dates

Paper submission deadline: February 17, 2017, 11:00 PM EST Author feedback: April 7-12, 2017 Author notification: May 5, 2017 Conference: July 7-10, 2017 (welcome reception on the 6th)

Committees

• Program Committee

Jake Abernethy (University of Michigan) Alekh Agarwal (Microsoft Research) Shipra Agarwal(Columbia University) Shivani Agarwal (University of Pennsylvania) Anima Anandkumar (University of California Irvine) Peter Auer (Montanuniversitaet Leoben) Pranjal Awasthi (Rutgers

• Program Chairs

Satyen Kale and Ohad Shamir