- talks - lists.cs.princeton.edu

Ankit Garg will present his Pre-FPO on Thursday, February 4, 2016 at 1:30 pm in CS 402. (UPDATE: change of committee member)
by Nicki Gotsis 02 Feb '16

02 Feb '16

Ankit Garg will present his Pre-FPO on Thursday, February 4 at 1:30 pm in CS 402. The members of his committee are Mark Braverman (adviser), Bernard Chazelle, Zeev Dvir, Ran Raz (IAS) and Avi Wigderson (IAS). Everyone is invited to attend his talk. The talk title and abstract follow below: Title: Information theoretic relaxations in complexity theory Abstract: Since Shannon’s “A Mathematical Theory of Communication”, information theory has found applicability in a wide range of scientific disciplines. Over the past two decades, information theory has reemerged in theoretical computer science as a mathematical tool with applications to streaming algorithms, data structures, communication complexity etc. In the first part of talk, I will talk about a new information theoretic framework for proving parallel repetition of 2-prover 1-round games. Using this framework, we can resolve the open question about parallel repetition of small value games. This is based on joint work with Mark Braverman. In the second part of the talk, I will talk about near optimal round-communication tradeoffs for quantum communication complexity of disjointness. The techniques involved in the proof include quantum information complexity and the self

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Sema Berkiten will present her Pre FPO on Monday, February 8, 2016 at 10:00am in CS 401
by Nicki Gotsis 02 Feb '16

02 Feb '16

Sema Berkiten will present her Pre FPO on Monday, February 8, 2016 at 10:00am in CS 401. The members of her committee are: Szymon Rusinkiewicz (adviser), Adam Finkelstein (reader), Hao Li (USC, reader), Thomas Funkhouser (non-reader) and David Dobkin (non-reader). Title: Capturing, Processing, and Synthesizing Surfaces with Details Abstract: Geometry acquisition has become increasingly popular in computer graphics and vision, with demand for high-quality models driven by advances in 3D printing, realistic real-time renderings of 3D characters in video games, digital libraries for historical objects etc. In this thesis, we focus on techniques to produce and process detailed geometry including acquisition of real world objects, processing and combining the captured data, and synthesizing new surfaces from existing ones. First, we summarize a 2D acquisition technique called photometric stereo to capture high resolution surface details. As a validation step, we solve a misalignment problem for photometric datasets which may be caused by perturbations to the camera or to the object, or the effect of optical image stabilization, especially in long photo shoots. After the dataset is validated, the surface normals can be computed using one of the photometric stereo algorithms. In order to decide which algorithm to use, we present a synthetic photometric benchmark to evaluate various algorithms for different scenarios. Next, we introduce a semi-automated system to convert photometric datasets into geometry-aware non-photorealistic illustrations of surface details that obey the common conventions of epigraphy (black-and-white archaeological drawings of inscriptions). This system is composed of rectification of the surface normals to correct camera perspective, segmentation of the inscriptions from the background, classification of the inscription based on carving technique (either slightly deeper grooves, or shallow pecked-out regions), and stylization of the inscriptions in various styles. To produce a detailed surface in 3D, we propose an approach to combine a rough 3D geometry with fine detailed normal maps obtained from different views. We begin with unaligned 2D normal maps and a rough 3D geometry, and automatically optimize the alignments through a two-step iterative registration algorithm to align each normal map to the 3D geometry. We then map the normals onto the surface, correct and seamlessly blend them together. At the end, we optimize the geometry to produce a high-quality 3D model that incorporates the high-frequency details from the normal maps. Finally, we present an algorithm for realistically transferring surface details (specifically, displacement maps) from existing high-quality 3D models to simple shapes that may be created with easy-to-learn modeling tools. Our key insight is to use metric learning to find a combination of geometric features that successfully predicts detail-map similarities on the source mesh, and use the learned feature combination to drive the detail transfer.

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REMINDER - You have to be brilliant to do that! Cultures of Brilliance and Academic Gender Gaps by Professor Sarah-Jane Leslie - Wednesday, February 3, 2016, 4:00 p.m., Maeder Hall Auditorium
by Nicole E. Wagenblast 02 Feb '16

02 Feb '16

You have to be brilliant to do that! Cultures of Brilliance and Academic Gender Gaps Professor Sarah-Jane Leslie Wednesday, February 3, 2016, 4:00 p.m. Maeder Hall Auditorium

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Ankit Garg will present his Pre-FPO on Thursday, February 4, 2016 at 1:30 pm in CS 402.
by Nicki Gotsis 28 Jan '16

28 Jan '16

Ankit Garg will present his Pre-FPO on Thursday, February 4 at 1:30 pm in CS 402. The members of his committee are Mark Braverman (adviser), Sanjeev Arora, Zeev Dvir, Ran Raz (IAS) and Avi Wigderson (IAS). Everyone is invited to attend his talk. The talk title and abstract follow below: Title: Information theoretic relaxations in complexity theory Abstract: Since Shannon’s “A Mathematical Theory of Communication”, information theory has found applicability in a wide range of scientific disciplines. Over the past two decades, information theory has reemerged in theoretical computer science as a mathematical tool with applications to streaming algorithms, data structures, communication complexity etc. In the first part of talk, I will talk about a new information theoretic framework for proving parallel repetition of 2-prover 1-round games. Using this framework, we can resolve the open question about parallel repetition of small value games. This is based on joint work with Mark Braverman. In the second part of the talk, I will talk about near optimal round-communication tradeoffs for quantum communication complexity of disjointness. The techniques involved in the proof include quantum information complexity and the self reducibility of disjointness. This is based on joint work with Mark Braverman, Young Kun Ko, Jieming Mao and Dave Touchette.

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CSML Seminar: David Dunson, Tomorrow, January 19, 2016 at 12:30pm | Computer Science, Room 105
by Nicole E. Wagenblast 18 Jan '16

18 Jan '16

David Dunson-Duke University Tuesday, January 19, 2016 12:30pm-1:30pm Computer Science, Room 105 * Lunch will be provided * Title: “Probabilistic inference from complex and high-dimensional data” Abstract: There is a well-known increasing trend in complexity and size of data being collected across fields. Although many approaches have been developed for analyzing such data, there is a clear lack of methods that are robust, computationally scalable, and provide realistic uncertainty quantification. We develop broad new tools for probabilistic inference from big and complex data along several threads, including a new framework for robust Bayesian inferences using coarsening, and new algorithms for scalable computation relying on (i) breaking data into subsets, estimating posterior probability measures for each subset and combining via Wasserstein barycenters; and (ii) approximate Markov chain Monte Carlo algorithms, which replace expensive transition kernels with approximations. We discuss theoretical results on robustness, computational complexity, and statistical accuracy and illustrate the methods with several applications. If you would like to be added to the CSML listerv, please email capizzi(a)princeton.edu .

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Colloquium Speaker Tom Griffiths, today, 12:30pm
by Nicole E. Wagenblast 15 Jan '16

15 Jan '16

Colloquium Speaker Tom Griffiths, University of California, Berkeley Friday, January 15, 12:30pm Computer Science 105 Human and machine learning Human cognition still sets the standard we aspire to in many areas of machine learning, including problems such as identifying causal relationships, acquiring and using language, and learning concepts from a small number of examples. In these cases, human and machine learning can establish a mutually beneficial relationship: we can use the formal tools developed in machine learning to provide insights into human learning, and translate those insights into new machine learning systems. I will use the case of causal induction to illustrate the value of this approach, but also highlight some applications in language and concept learning. I will also argue that the same kind of mutually beneficial relationship could potentially exist between developing data-intensive approaches to cognitive science and making sense of large volumes of behavioral data in computer science.

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Colloquium Speaker Tom Griffiths, Fri Jan 15, 12:30pm
by Nicole E. Wagenblast 14 Jan '16

14 Jan '16

Colloquium Speaker Tom Griffiths, University of California, Berkeley Friday, January 15, 12:30pm Computer Science 105 Human and machine learning Human cognition still sets the standard we aspire to in many areas of machine learning, including problems such as identifying causal relationships, acquiring and using language, and learning concepts from a small number of examples. In these cases, human and machine learning can establish a mutually beneficial relationship: we can use the formal tools developed in machine learning to provide insights into human learning, and translate those insights into new machine learning systems. I will use the case of causal induction to illustrate the value of this approach, but also highlight some applications in language and concept learning. I will also argue that the same kind of mutually beneficial relationship could potentially exist between developing data-intensive approaches to cognitive science and making sense of large volumes of behavioral data in computer science.

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Colloquium Speaker Tom Griffiths, Fri Jan 15, 12:30pm
by Nicole E. Wagenblast 12 Jan '16

12 Jan '16

Colloquium Speaker Tom Griffiths, University of California, Berkeley Friday, January 15, 12:30pm Computer Science 105 Human and machine learning Human cognition still sets the standard we aspire to in many areas of machine learning, including problems such as identifying causal relationships, acquiring and using language, and learning concepts from a small number of examples. In these cases, human and machine learning can establish a mutually beneficial relationship: we can use the formal tools developed in machine learning to provide insights into human learning, and translate those insights into new machine learning systems. I will use the case of causal induction to illustrate the value of this approach, but also highlight some applications in language and concept learning. I will also argue that the same kind of mutually beneficial relationship could potentially exist between developing data-intensive approaches to cognitive science and making sense of large volumes of behavioral data in computer science.

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Soumyadeep Ghosh will present his Pre-FPO, "Hardware Assurance with Pluggable Trust Architectures" on Friday, January 15, 2016 at 3:30pm in CS 301
by Nicki Gotsis 11 Jan '16

11 Jan '16

Soumyadeep Ghosh will present his Pre-FPO on Friday, January 15, 2016 at 3:30pm in CS 301. The members of his committee are David August (advisor), Andrew Appel and Aarti Gupta (readers), David Wentzlaff and Simha Sethumadhavan, Columbia University (non-readers). Everyone is invited to attend his talk. The talk title and abstract follow below: Title: Hardware Assurance with Pluggable Trust Architectures Abstract: Today, a user must take it on faith that their hardware and software providers have built a system which will not betray them to malicious actors. While significant research has been done on securing the software stack, these techniques all assume the presence of secure hardware. However, a number of factors such as incompleteness of techniques for verifying complex hardware designs, outsourcing and off-shoring of design and fabrication, and the incorporation of third-party components diminish confidence in the security of computer hardware. To address this problem, we propose a new architecture that allows users to select their own basis of trust in the system, independent of the device manufacturer. Trust is established via a pluggable and user-swappable hardware element called the Sentry. This pluggable-trust architecture isolates the effects of compromised hardware by allowing only the correctly executed results of signed software to be communicated externally. The basis of trust for the entire system is the Sentry, which acts as a gatekeeper and bridges the physical gap between the untrusted processor and any I/O device. The Sentry’s minimal effect on performance, the simplicity of its design, and its pluggability enable its production at an independent trusted fabrication plant. Its simplicity also makes the Sentry's verification tractable, giving the user choice in trust providers.

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Sarthak Grover will present his General Exam on Friday, January 8, 2016 in CS 302 at 2pm.
by Nicki Gotsis 06 Jan '16

06 Jan '16

Sarthak Grover will present his General Exam on Friday, January 8, 2016 in CS 302 at 2pm. The members of his committee are Nick Feamster (Adviser), Kyle Jamieson, and Jennifer Rexford. Everyone is invited to attend his talk, and those faculty wishing to remain for the oral exam following are welcome to do so. His abstract and reading list follow below. *Abstract* With a large increase in broadband services and capacity, it has become important to understand home network infrastructure and usage. Over the past two years, we have studied home network usage from two perspectives: the gateway and the ISP. In the first empirical study of home network availability, infrastructure, and usage, we deployed routers running custom firmware in multiple homes to collect measurements of home and Internet connectivity, as well as how users use their home network. Our results showed that half the home networks studied utilize less than half their available capacity. We followed up to this work by studying the relationship between traffic demand and service tier upgrades from the perspective of ISPs. In a unique controlled experiment, we compare two groups of Comcast subscribers from the same city: a control group (105 Mbps) and a randomly selected treatment group that was upgraded to 250 Mbps without their knowledge. We study how users who are already on service plans with high downstream throughput respond to a higher service tier (upgraded unknowingly), as compared to a similar control group. To our surprise, subscribers with moderate traffic demands increase their usage in response to a service-tier upgrade relatively more than high-volume subscribers do. We speculate that even though these users may not take advantage of the full available capacity, the service tier increase generally improves performance, which causes them to use the Internet more than they otherwise would have. *Reading List* 1. Bischof, Zachary S., Fabián E. Bustamante, and Rade Stanojevic. "Need, want, can afford: Broadband markets and the behavior of users." In Proceedings of the 2014 Conference on Internet Measurement Conference, pp. 73-86. ACM, 2014. 2. Kreibich, Christian, Nicholas Weaver, Boris Nechaev, and Vern Paxson. "Netalyzr: illuminating the edge network." In Proceedings of the 10th ACM SIGCOMM conference on Internet measurement, pp. 246-259. ACM, 2010. 3. Quan, Lin, John Heidemann, and Yuri Pradkin. "When the internet sleeps: correlating diurnal networks with external factors." In Proceedings of the 2014 Conference on Internet Measurement Conference, pp. 87-100. ACM, 2014. 4.Maier, Gregor, Anja Feldmann, Vern Paxson, and Mark Allman. "On dominant characteristics of residential broadband internet traffic." InProceedings of the 9th ACM SIGCOMM conference on Internet measurement conference, pp. 90-102. ACM, 2009. 5. Dicioccio, Lucas, Renata Teixeira, and Catherine Rosenberg. "Measuring home networks with homenet profiler." In Passive and Active Measurement, pp. 176-186. Springer Berlin Heidelberg, 2013. 6.Zheleva, Mariya, Paul Schmitt, Morgan Vigil, and Elizabeth Belding. "The increased bandwidth fallacy: performance and usage in rural zambia." InProceedings of the 4th Annual Symposium on Computing for Development, p. 2. ACM, 2013. 7.Cho, Kenjiro, Kensuke Fukuda, Hiroshi Esaki, and Akira Kato. "The impact and implications of the growth in residential user-to-user traffic." In ACM SIGCOMM Computer Communication Review, vol. 36, no. 4, pp. 207-218. ACM, 2006. 8.Paxson, Vern. "End-to-end routing behavior in the Internet." Networking, IEEE/ACM Transactions on 5, no. 5 (1997): 601-615. 9.Paxson, Vern. "Strategies for sound internet measurement." In Proceedings of the 4th ACM SIGCOMM conference on Internet measurement, pp. 263-271. ACM, 2004. 10.Calvert, Kenneth L., W. Keith Edwards, and Rebecca E. Grinter. "Moving Toward the Middle: The Case Against the End-to-End Argument in Home Networking." In HotNets. 2007. 11.Sundaresan, Srikanth, Walter De Donato, Nick Feamster, Renata Teixeira, Sam Crawford, and Antonio Pescapè. "Broadband internet performance: a view from the gateway." In ACM SIGCOMM computer communication review, vol. 41, no. 4, pp. 134-145. ACM, 2011. 12.Peterson, Larry L., and Bruce S. Davie. Computer networks: a systems approach. Elsevier, 2007. 13.Grover, Sarthak, Mi Seon Park, Srikanth Sundaresan, Sam Burnett, Hyojoon Kim, Bharath Ravi, and Nick Feamster. "Peeking behind the NAT: an empirical study of home networks." In Proceedings of the 2013 conference on Internet measurement conference, pp. 377-390. ACM, 2013. 14.Grover, Sarthak, Roya Ensafi, and Nick Feamster. “A case study of traffic demand response to broadband service-plan upgrades.” In Proceedings of the 2016 Passive and Active Measurement Conference. 2016.

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