School of Technology and Computer Science - A-201 and Zoom
https://brahma.tcs.tifr.res.in/venue/201-and-zoom
enLearning Optimal Bids in Second Price Auctions with Temporal and Overlapping Targeting Constraints
https://brahma.tcs.tifr.res.in/events/learning-optimal-bids-second-price-auctions-temporal-and-overlapping-targeting-constraints
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<a href="/event/stcs-seminar" typeof="skos:Concept" property="rdfs:label skos:prefLabel" datatype="">STCS Seminar</a> </li>
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<section class="field field-name-field-other field-type-text-long field-label-inline clearfix view-mode-rss"><h2 class="field-label">Speaker: </h2><div class="field-items"><div class="field-item even">Ravi R. Mazumdar </div></div></section><section class="field field-name-field-affiliation field-type-text-long field-label-inline clearfix view-mode-rss"><h2 class="field-label">Affiliation: </h2><div class="field-items"><div class="field-item even"><p>University of Waterloo</p>
</div></div></section><section class="field field-name-field-time field-type-datetime field-label-inline clearfix view-mode-rss"><h2 class="field-label">Time: </h2><div class="field-items"><div class="field-item even"><span class="date-display-single">Monday, 25 July 2022, <span class="date-display-range"><span class="date-display-start" property="dc:date" datatype="xsd:dateTime" content="2022-07-25T16:00:00+05:30">16:00</span> to <span class="date-display-end" property="dc:date" datatype="xsd:dateTime" content="2022-07-25T17:00:00+05:30">17:00</span></span></span></div></div></section><section class="field field-name-field-venue field-type-taxonomy-term-reference field-label-inline clearfix view-mode-rss clearfix">
<h2 class="field-label">Venue: </h2>
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<a href="/venue/201-and-zoom" typeof="skos:Concept" property="rdfs:label skos:prefLabel" datatype="">A-201 and Zoom</a> </li>
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<section class="field field-name-field-organisers field-type-entityreference field-label-inline clearfix view-mode-rss"><h2 class="field-label">Organisers: </h2><div class="field-items"><div class="field-item even"><a href="/people/abhishek-sinha">Abhishek Sinha</a></div></div></section><div class="field field-name-body field-type-text-with-summary field-label-hidden view-mode-rss"><div class="field-items"><div class="field-item even" property="content:encoded"><p>Ad placement in web-browsing and wireless mobiles is an increasingly important component of the advertisement market. The market size is over $ 100 billion and counting. The mechanism is as follows: when a user opens a webpage or mobile ap a message is sent to an exchange where multiple bidders have the possibility of placing an ad that would target the right user, eg. age, sex, location, etc. The ad that is displayed corresponds to the bidder who bids the highest while the cost is calculated according to a first or second price. Typically bidders are DSP (Demand Side Platforms) that aggregate bids on behalf of clients who wish to run a campaign for a given length of time with certain targeting criteria. The goal is to minimize the total cost of obtaining the required number of impressions (ads that meet targeting criteria) over the duration of a contract. The real time constraint is that bidding must be done within 100ms.</p>
<p> In this talk I will build upon the theory that we had earlier developed for computing the least cost bids in the second price context. This involves the notion of an information state for the problem. There is a very rich primal-dual theory that emerges, one in the so called impressions space and the other in the contracts space. Computationally and structurally the primal and dual views of the optimization have different properties that can be exploited to come up with fast algorithms.</p>
<p> The optimal solutions depend on solving a constrained convex optimization problem when the information state is known. However this is not readily available and thus there is the problem of learning the information state. We show that in the second price case, stochastic approximation (SA) algorithms that operate on censored data (prices are only known by a bidder when the bidder wins) can be devised that solve the constrained optimization problem without learning the information state explicitly and we prove their convergence. Finally I will present the dynamic behaviour through simulations.</p>
<p>Joint work with Ryan Kinnear (Waterloo) and Peter Marbach (Toronto). We thank Addictive Mobility Inc., a Pelmorex company for having proposed the problem and to Addictive Mobility, Ontario OCE VIP II, and NSERC funding the work.</p>
<p> Bio: The speaker was educated at the Indian Institute of Technology, Bombay (B.Tech, 1977), Imperial College, London (MSc, DIC, 1978) and obtained his PhD in Control Theory under A. V. Balakrishnan at UCLA in 1983. He is currently a University Research Chair Professor in the Dept. of ECE at the University of Waterloo, Ont., Canada where he has been since September 2004. Prior to this he was Professor of ECE at Purdue University, West Lafayette, USA. Since 2012 he is a D.J. Gandhi Distinguished Visiting Professor at the Indian Institute of Technology, Bombay, India and since May 2019 an Adjunct Professor at the Tata Institute of Fundamental Research (TIFR), Mumbai. He is a Fellow of the IEEE and the Royal Statistical Society. He is a recipient of the INFOCOM 2006 Best Paper Award, the ITC-27 2015 Best Paper Award, the Performance 2015 Best Paper Award and was runner-up for the Best Paper Award at INFOCOM 1998. His research interests are in stochastic modelling and analysis applied to complex networks and statistical inference.</p>
<p>YouTube Link: <a href="https://youtu.be/dA44DA8gQDM">https://youtu.be/dA44DA8gQDM</a></p>
</div></div></div><section class="field field-name-field-diplay-profile field-type-list-boolean field-label-above view-mode-rss"><h2 class="field-label">Faculty Candidate: </h2><div class="field-items"><div class="field-item even"></div></div></section>Mon, 18 Jul 2022 06:29:14 +0000Supriya Pottipati4694 at https://brahma.tcs.tifr.res.inTechno-Economic Optimization Problems Related to 5G Technology
https://brahma.tcs.tifr.res.in/events/techno-economic-optimization-problems-related-5g-technology
<div class="field field-name-field-event-type field-type-taxonomy-term-reference field-label-hidden view-mode-rss clearfix">
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<a href="/event/stcs-seminar" typeof="skos:Concept" property="rdfs:label skos:prefLabel" datatype="">STCS Seminar</a> </li>
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<section class="field field-name-field-other field-type-text-long field-label-inline clearfix view-mode-rss"><h2 class="field-label">Speaker: </h2><div class="field-items"><div class="field-item even">Gourav Saha </div></div></section><section class="field field-name-field-affiliation field-type-text-long field-label-inline clearfix view-mode-rss"><h2 class="field-label">Affiliation: </h2><div class="field-items"><div class="field-item even"><p>Purdue University</p>
</div></div></section><section class="field field-name-field-time field-type-datetime field-label-inline clearfix view-mode-rss"><h2 class="field-label">Time: </h2><div class="field-items"><div class="field-item even"><span class="date-display-single">Thursday, 16 June 2022, <span class="date-display-range"><span class="date-display-start" property="dc:date" datatype="xsd:dateTime" content="2022-06-16T16:00:00+05:30">16:00</span> to <span class="date-display-end" property="dc:date" datatype="xsd:dateTime" content="2022-06-16T17:00:00+05:30">17:00</span></span></span></div></div></section><section class="field field-name-field-venue field-type-taxonomy-term-reference field-label-inline clearfix view-mode-rss clearfix">
<h2 class="field-label">Venue: </h2>
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<a href="/venue/201-and-zoom" typeof="skos:Concept" property="rdfs:label skos:prefLabel" datatype="">A-201 and Zoom</a> </li>
</ul>
</section>
<section class="field field-name-field-organisers field-type-entityreference field-label-inline clearfix view-mode-rss"><h2 class="field-label">Organisers: </h2><div class="field-items"><div class="field-item even"><a href="/people/rahul-vaze">Rahul Vaze</a></div></div></section><div class="field field-name-body field-type-text-with-summary field-label-hidden view-mode-rss"><div class="field-items"><div class="field-item even" property="content:encoded"><p>Spectrum sharing and Millimeter Wave Communication are two promising technologies for 5G and beyond communication. In a spectrum sharing market, the regulator (the government) and the wireless service providers are two important stakeholders. In this talk, I will focus mainly on spectrum sharing from the perspective of the regulator.</p>
<p>One of the objectives of the regulator is to maximize the utilization of the spectrum band. I will discuss a Stackelberg game framework to optimize various parameters of the spectrum market in order to maximize spectrum utilization. These parameters include (i) the duration of a spectrum license, (ii) the number of spectrum bands, and (iii) the ratio of the licensed and unlicensed spectrum bands. Out of these three parameters, optimizing the duration of spectrum license is my most novel contribution and hence I will discuss this topic. Optimizing the duration of spectrum license involves solving a Stackelberg game. I will discuss an O(log(T)) algorithm to solve the Stackelberg game, T being the maximum lease duration, while the brute-force approach has a time complexity of O(T). I will also briefly discuss a combinatorial optimization viewpoint of solving the Stackelberg Game.</p>
<p>I will also briefly talk about a variant of the Ski-Rental problem that we solved while addressing a challenge faced by wireless service provider while operating in a spectrum sharing market. I will also briefly discuss my work on designing scheduling algorithms for millimeter-wave communication by using tools from partially observable Markov decision processes. Finally, I will end the seminar with future research plans related to (i) a variant of multi-armed bandits for directional millimeter-wave communication, and (ii) spectrum enforcement for spectrum sharing.</p>
<p> <strong>Bio: </strong>Gourav Saha received a B.E. degree from Anna University, Chennai, India, in 2012, M.S. from Indian Institute of Technology Madras, India, in 2015, and Ph.D. from Rensselaer Polytechnic Institute, Troy, New York, in 2020, all in electrical engineering and allied areas. He is currently a postdoctoral scholar in the Department of Electrical and Computer Engineering of Purdue University and was previously a postdoctoral scholar at Ohio State University. His research experience includes control systems, online algorithms, game theory, the economics of wireless spectrum sharing market, and Markov decision process. His current research involves designing scheduling and learning algorithms for millimeter-wave communication.</p>
</div></div></div><section class="field field-name-field-diplay-profile field-type-list-boolean field-label-above view-mode-rss"><h2 class="field-label">Faculty Candidate: </h2><div class="field-items"><div class="field-item even"></div></div></section>Mon, 06 Jun 2022 08:55:21 +0000Supriya Pottipati4670 at https://brahma.tcs.tifr.res.inData-derived weak universal consistency for lossless compression
https://brahma.tcs.tifr.res.in/events/data-derived-weak-universal-consistency-lossless-compression
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<a href="/event/stcs-seminar" typeof="skos:Concept" property="rdfs:label skos:prefLabel" datatype="">STCS Seminar</a> </li>
</ul>
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<section class="field field-name-field-other field-type-text-long field-label-inline clearfix view-mode-rss"><h2 class="field-label">Speaker: </h2><div class="field-items"><div class="field-item even">Venkat Anantharam</div></div></section><section class="field field-name-field-affiliation field-type-text-long field-label-inline clearfix view-mode-rss"><h2 class="field-label">Affiliation: </h2><div class="field-items"><div class="field-item even"><p>University of California, Berkeley</p>
</div></div></section><section class="field field-name-field-time field-type-datetime field-label-inline clearfix view-mode-rss"><h2 class="field-label">Time: </h2><div class="field-items"><div class="field-item even"><span class="date-display-single">Thursday, 2 June 2022, <span class="date-display-range"><span class="date-display-start" property="dc:date" datatype="xsd:dateTime" content="2022-06-02T16:00:00+05:30">16:00</span> to <span class="date-display-end" property="dc:date" datatype="xsd:dateTime" content="2022-06-02T17:00:00+05:30">17:00</span></span></span></div></div></section><section class="field field-name-field-venue field-type-taxonomy-term-reference field-label-inline clearfix view-mode-rss clearfix">
<h2 class="field-label">Venue: </h2>
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<a href="/venue/201-and-zoom" typeof="skos:Concept" property="rdfs:label skos:prefLabel" datatype="">A-201 and Zoom</a> </li>
</ul>
</section>
<section class="field field-name-field-organisers field-type-entityreference field-label-inline clearfix view-mode-rss"><h2 class="field-label">Organisers: </h2><div class="field-items"><div class="field-item even"><a href="/people/vinod-m-prabhakaran">Vinod M. Prabhakaran</a></div></div></section><div class="field field-name-body field-type-text-with-summary field-label-hidden view-mode-rss"><div class="field-items"><div class="field-item even" property="content:encoded"><p>Rich model classes for data may be too complex to admit uniformly consistent estimators. In such cases, it is conventional to settle for pointwise consistent estimators. But this viewpoint has the practical drawback that estimator performance is a function of the unknown model within the model class that is being estimated. Even if an estimator is consistent, how well it is doing at any given time may not be clear, no matter what the sample size of the observations.</p>
<p>We explore how to resolve this issue by studying model classes that may only admit pointwise consistency guarantees, yet enough information about the unknown model driving the observations needed to gauge estimator accuracy can be inferred from the sample at hand. We would then say that such model classes admit data-derived weak universally consistent estimators.</p>
<p>In this work we flesh out this philosophy in the framework of lossless data compression problems over a countable alphabet. Our main contribution is to characterize the model classes that admit data-derived weak universally consistent lossless compression in terms of the presence or not of what we term deceptive distributions (whether a distribution is deceptive or not is defined in the context of the model class). We also show that the ability to estimate the redundancy of compressing memoryless sources is equivalent to learning the underlying single-letter marginal in a data-derived fashion.</p>
<p>This is joint work with Narayana Prasad Santhanam and Wojtek Szpankowski.</p>
<p>Bio: Venkat Anantharam is on the faculty of the EECS department at U. C. Berkeley. He received his B. Tech. (1980) in Electrical Engineering (Electronics) from IIT Madras, and the M.S. (1982) and Phd. (1986) in Electrical Engineering and M.A. (1984) and C. Phil. (1985) in Mathematics from U. C. Berkeley. From 1986 to 1994 he was on the faculty of the School of EE at Cornell University. He has been with the EECS department at U. C. Berkeley since 1994. He is a Fellow of the IEEE and a Distinguished Alumnus of IIT Madras.</p>
</div></div></div><section class="field field-name-field-diplay-profile field-type-list-boolean field-label-above view-mode-rss"><h2 class="field-label">Faculty Candidate: </h2><div class="field-items"><div class="field-item even"></div></div></section>Tue, 31 May 2022 05:36:36 +0000Supriya Pottipati4668 at https://brahma.tcs.tifr.res.inFast multivariate multipoint evaluation over finite fields
https://brahma.tcs.tifr.res.in/events/fast-multivariate-multipoint-evaluation-over-finite-fields
<div class="field field-name-field-event-type field-type-taxonomy-term-reference field-label-hidden view-mode-rss clearfix">
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<a href="/event/stcs-seminar" typeof="skos:Concept" property="rdfs:label skos:prefLabel" datatype="">STCS Seminar</a> </li>
</ul>
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<section class="field field-name-field-other field-type-text-long field-label-inline clearfix view-mode-rss"><h2 class="field-label">Speaker: </h2><div class="field-items"><div class="field-item even">Mrinal Kumar</div></div></section><section class="field field-name-field-affiliation field-type-text-long field-label-inline clearfix view-mode-rss"><h2 class="field-label">Affiliation: </h2><div class="field-items"><div class="field-item even"><p>Indian Institute of Technology Bombay</p>
</div></div></section><section class="field field-name-field-time field-type-datetime field-label-inline clearfix view-mode-rss"><h2 class="field-label">Time: </h2><div class="field-items"><div class="field-item even"><span class="date-display-single">Monday, 30 May 2022, <span class="date-display-range"><span class="date-display-start" property="dc:date" datatype="xsd:dateTime" content="2022-05-30T11:00:00+05:30">11:00</span> to <span class="date-display-end" property="dc:date" datatype="xsd:dateTime" content="2022-05-30T12:00:00+05:30">12:00</span></span></span></div></div></section><section class="field field-name-field-venue field-type-taxonomy-term-reference field-label-inline clearfix view-mode-rss clearfix">
<h2 class="field-label">Venue: </h2>
<ul class="field-items">
<li class="field-item even">
<a href="/venue/201-and-zoom" typeof="skos:Concept" property="rdfs:label skos:prefLabel" datatype="">A-201 and Zoom</a> </li>
</ul>
</section>
<section class="field field-name-field-organisers field-type-entityreference field-label-inline clearfix view-mode-rss"><h2 class="field-label">Organisers: </h2><div class="field-items"><div class="field-item even"><a href="/people/jaikumar-radhakrishnan">Jaikumar Radhakrishnan</a></div></div></section><div class="field field-name-body field-type-text-with-summary field-label-hidden view-mode-rss"><div class="field-items"><div class="field-item even" property="content:encoded"><p>Multipoint evaluation is the computational task of evaluating a polynomial given as a list of coefficients at a given set of inputs. A straightforward algorithm for this problem is to just iteratively evaluate the polynomial at each of the inputs. The question of obtaining faster-than-naive (and ideally, close to linear time) algorithms for this problem is a natural and fundamental question in computational algebra. In addition to its own inherent interest, faster algorithms for multipoint evaluation are closely related to fast algorithms for other natural algebraic questions like polynomial factorization and modular composition.</p>
<p>Nearly linear time algorithms have been known for the univariate multipoint evaluation for close to five decades due to a work of Borodin and Moenck but fast algorithms for the multivariate (or, even bivariate) version have been much harder to come by. In a significant improvement to the state of art for this problem in 2008, Umans and Kedlaya-Umans gave nearly linear time algorithms for this problem over field of small characteristic and over all finite fields respectively, provided that the number of variables is at most d^{o(1)} where d is the degree of the input polynomial in every variable.</p>
<p>In this talk, we will discuss two new algorithms for this problem: the first is a simple and natural algebraic algorithm over not-too-large fields of small characteristic and the second is a (non-algebraic) algorithm for this problem over all finite fields. Both these algorithms run in nearly linear time even when the number of variables is large. We will also discuss an application to an upper bound for data structures for polynomial evaluation and to an upper bound on the rigidity of Vandermonde matrices.</p>
<p>The talk is based on joint works with Vishwas Bhargava, Sumanta Ghosh, Zeyu Guo, Chandra Kanta Mohapatra and Chris Umans.</p>
</div></div></div><section class="field field-name-field-diplay-profile field-type-list-boolean field-label-above view-mode-rss"><h2 class="field-label">Faculty Candidate: </h2><div class="field-items"><div class="field-item even"></div></div></section>Fri, 20 May 2022 05:32:44 +0000Supriya Pottipati4665 at https://brahma.tcs.tifr.res.in