Difference between revisions of "COLT 2017"
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{{Event | {{Event | ||
| − | |||
|Acronym=COLT 2017 | |Acronym=COLT 2017 | ||
| + | |Title=30th Annual Conference on Learning Theory | ||
|Series=COLT | |Series=COLT | ||
| − | |End date=10/07/ | + | |Type=Conference |
| + | |Field=Computational Learning Theory | ||
| + | |Start date=2017/07/07 | ||
| + | |End date=2017/10/07 | ||
| + | |Homepage=http://www.learningtheory.org/colt2017/ | ||
|City=Amsterdam | |City=Amsterdam | ||
|Country=Netherlands | |Country=Netherlands | ||
| − | | | + | |Submitted papers=228 |
| − | | | + | |Accepted papers=73 |
| − | | | + | |has Proceedings Link=http://proceedings.mlr.press/v65/ |
}} | }} | ||
| + | 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 | ||
| + | |||
| + | ==Submissions== | ||
| + | ==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 | ||
Revision as of 14:47, 21 May 2019
| 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... | |
| 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
Submissions
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
| Acceptance rate | 32.0 + |
| Accepted papers | 73 + |
| Acronym | COLT 2017 + |
| Attendance fee currency | € + |
| Early bird regular | 250.00 + |
| Early bird student | 150.00 + |
| End date | October 7, 2017 + |
| Event in series | COLT + |
| Event type | Conference + |
| Has coordinates | 52° 22' 23", 4° 53' 33"Latitude: 52.373080555556 Longitude: 4.8924527777778 + |
| Has location city | Amsterdam + |
| Has location country | Category:Netherlands + |
| Homepage | http://www.learningtheory.org/colt2017/ + |
| IsA | Event + |
| On site regular | 600.00 + |
| On site student | 350.00 + |
| Start date | July 7, 2017 + |
| Submitted papers | 228 + |
| Title | 30th Annual Conference on Learning Theory + |
