- talks - lists.cs.princeton.edu

Colloquium Speaker: Asaf Cidon, Friday, March 3 - 12:30pm Reminder
by Nicole E. Wagenblast 02 Mar '17

02 Mar '17

Colloquium Speaker Asaf Cidon, Stanford University Friday, March 3 - 12:30pm Computer Science 105 Host: Prof. Kyle Jamieson Reliability and Performance Challenges at Cloud Scale Cloud computing is quickly becoming the backbone for critical societal applications, such as self-driving cars, tele-medicine and Internet of Things. However, the unprecedented scale of cloud infrastructure, with millions of servers spread across hundreds of data centers, introduces new fundamental challenges that were not faced by past computer systems. In my talk, I will present two examples of systems, Copysets and Cliffhanger, which leverage an analytical approach to tackle novel challenges introduced by the scale of the cloud. In Copysets, I present a novel replication framework that reduces the probability of data loss by over 10,000 times for the common scenario of simultaneous server failures. In Cliffhanger, I present a key-value cache that dynamically adapts to changing cloud application workloads, which reduces the number of misses by 35% or more. Both of these systems provide an example for my research approach, of building practical systems that tackle novel unstudied problems introduced by the scale of the cloud. Asaf Cidon is the Vice President, Content Security Services at Barracuda Networks. He currently also leads the cloud caching research project at Stanford. Asaf completed his PhD at Stanford under Mendel Rosenblum and Sachin Katti. His research on cloud and mobile systems was published in NSDI and Sigcomm, and received the Best Student Paper Award in Usenix ATC. Asaf was also the founder and CEO of Sookasa, a cloud storage security startup, which was acquired by Barracuda Networks. His research focuses on how to provide reliability and performance guarantees in large-scale cloud environments, and was adopted by several companies, including Facebook, NetApp, and Chartbeat.

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Colloquium Speaker: Irene Zhang, Today- 12:30pm
by Nicole E. Wagenblast 02 Mar '17

02 Mar '17

Colloquium Speaker Irene Zhang, University of Washington Thursday, March 2, 2017 - 12:30pm Computer Science 105 Host: Jennifer Rexford Towards New Systems for Mobile/Cloud Applications The proliferation of datacenters, smartphones, personal sensing and tracking devices, and home automation products is fundamentally changing the applications we interact with daily. Today's popular user applications are no longer limited to a single desktop computer but now commonly span many mobile devices and cloud servers. As a result, existing systems often do not meet the needs of modern mobile/cloud applications. In this talk, I will present three systems designed to tackle the challenges of mobile/cloud applications: Sapphire, Diamond and TAPIR. These systems represent a first step towards better end-to-end support for mobile/cloud applications in runtime management, data management, and distributed transactional storage. Together, they significantly simplify the development of new mobile/cloud applications. Irene Zhang is a fifth-year PhD student at the University of Washington. She works with Hank Levy and Arvind Krishnamurthy in the Computer Systems Lab. Her current research focuses on systems for large-scale, distributed applications, including distributed runtime systems and transactional storage systems. Before starting her PhD, Irene worked for three years at VMware in the virtual machine monitor group. Irene received her S.B. and M. Eng. in computer science from MIT, where she worked with Frans Kaashoek in the Parallel and Distributed Operating Systems Lab.

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Colloquium Speaker: Irene Zhang, Thursday, March 2- 12:30pm- reminder
by Nicole E. Wagenblast 01 Mar '17

01 Mar '17

Colloquium Speaker Irene Zhang, University of Washington Thursday, March 2, 2017 - 12:30pm Computer Science 105 Host: Jennifer Rexford Towards New Systems for Mobile/Cloud Applications The proliferation of datacenters, smartphones, personal sensing and tracking devices, and home automation products is fundamentally changing the applications we interact with daily. Today's popular user applications are no longer limited to a single desktop computer but now commonly span many mobile devices and cloud servers. As a result, existing systems often do not meet the needs of modern mobile/cloud applications. In this talk, I will present three systems designed to tackle the challenges of mobile/cloud applications: Sapphire, Diamond and TAPIR. These systems represent a first step towards better end-to-end support for mobile/cloud applications in runtime management, data management, and distributed transactional storage. Together, they significantly simplify the development of new mobile/cloud applications. Irene Zhang is a fifth-year PhD student at the University of Washington. She works with Hank Levy and Arvind Krishnamurthy in the Computer Systems Lab. Her current research focuses on systems for large-scale, distributed applications, including distributed runtime systems and transactional storage systems. Before starting her PhD, Irene worked for three years at VMware in the virtual machine monitor group. Irene received her S.B. and M. Eng. in computer science from MIT, where she worked with Frans Kaashoek in the Parallel and Distributed Operating Systems Lab.

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Talk by Alex Berg on Monday March 6
by Thomas Funkhouser 28 Feb '17

28 Feb '17

PIXL Lunch Talk Speaker: *Alex Berg* Date: Monday, March 06, 2017 Time: 12:30-1:30PM (lunch is served) Location: CS 402 *Title**: *Rethinking object detection in computer vision *Abstract: *Object detection is one of the core problems in computer vision and is a lens through which to view the field. It brings together machine learning (classification, regression) with the variation in appearance of objects and scenes with pose and articulation (lighting, geometry) , and the difficulty of what to recognize for what purpose (semantics) all in a setting where computational complexity is not something to talk about in abstract terms, but matters every millisecond for inference and where it can take exaflops to train a model (computation). I will talk about our ongoing work attacking all fronts of the detection problem. One is the speed-accuracy trade-off, which determines the settings where it is reasonably possible to use detection. Our work on single shot detection (SSD) is currently the leading approach [1,2]. Another direction is moving beyond detecting the presence and location of an object to detecting 3D pose. We are working on both learning deep-network models of how visual appearance changes with pose and object [3], as well as integrating pose estimation as a first class element in detection [4]. One place where pose is especially important is for object detection in the world around us, e.g in robotics, as opposed to on isolated internet images without context. I call this setting "situated recognition". A key illustration that this setting is under addressed is the lack of work in computer vision on the problem of active vision, where perception is integrated in a loop with sensor platform motion, a key challenge in robotics. I will present our work on a new approach to collecting datasets for training and evaluating situated recognition, allowing computer vision researchers to study active vision, for instance training networks using reinforcement learning on a densely sampled data of real RGBD imagery without the difficulty of operating a robot in the training loop. This is a counterpoint to recent work using simulation and CG for such reinforcement learning, where our use of real images allows studying and evaluating real-world perception. I will also briefly mention our lower-level work on computation for computer vision and deep learning algorithms and building tools for implementation on GPUS and fPGAs, as well as other ongoing projects. Collaborators for major parts of this talk UNC Students- Wei Liu, Cheng-Yang Fu, Phil Ammirato, Ric Poirson, Eunbyung Park Outside academic collaborator- Prof. Jana Kosecka (George Mason University) Adobe: Duygu Ceylan, Jimei Yang, Ersin Yumer; Google: Dragomir Anguelov, Dumitru Erhan, Christian Szegedy, Scott Reed Amazon: Ananth Ranga, Ambrish Tyagi [1] SSD: Single Shot MultiBox Detector Wei Liu, Dragomir Anguelov, Dumitru Erhan, Christian Szegedy, Scott Reed, Cheng-Yang Fu, Alexander C. Berg ECCV 2016 https://arxiv.org/pdf/1512.02325.pdf [2] DSSD : Deconvolutional Single Shot Detector Cheng-Yang Fu, Wei Liu, Ananth Ranga, Ambrish Tyagi, and Alexander C. Berg arXiv preprint arXiv:1701.06659 https://arxiv.org/pdf/1701.06659.pdf [3] Transformation-Grounded Image Generation Network for Novel 3D View Synthesis Eunbyung Park, Jimei Yang, Ersin Yumer, Duygu Ceylan, Alexander C. Berg To appear CVPR 2017 [4] Fast Single Shot Detection and Pose Estimation Patrick Poirson, Philip Ammirato, Cheng-Yang Fu, Wei Liu, Jana Kosecka, Alexander C. Berg 3DV 2016 https://arxiv.org/pdf/1609.05590 [5] A Dataset for Developing and Benchmarking Active Vision Phil Ammirato,Patrick Poirson, Eunbyung Park, Jana Kosecka, and Alexander C. Berg to appear ICRA 2017 *Bio: *Alex Berg's research concerns computational visual recognition. His work addresses aspects of computer, human, and robot vision. He has worked on general object recognition in images, action recognition in video, human pose identification in images, image parsing, face recognition, image search, and large-scale machine learning. He co-organizes the ImageNet Large Scale Visual Recognition Challenge, and organized the first Large-Scale Learning for Vision workshop. He is currently an associate professor in computer science at UNC Chapel Hill. Prior to that he was on the faculty at Stony Brook University, a research scientist at Columbia University, and research scientist at Yahoo! Research. His PhD at U.C. Berkeley developed a novel approach to deformable template matching. He earned a BA and MA in Mathematics from Johns Hopkins University and learned to race sailboats at SSA in Annapolis. In 2013, his work received the Marr prize. https://scholar.google.com/citations?user=jjEht8wAAAAJ&pagesize=100 http://acberg.com/

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Colloquium Speaker: Dan Ports, Monday, March 6- 12:30pm
by Nicole E. Wagenblast 28 Feb '17

28 Feb '17

Colloquium Speaker Dan Ports, University of Washington Monday, March 6 - 12:30pm Computer Science 105 Host: Prof. Michael Freedman Rethinking Distributed Systems for the Datacenter Today's most popular applications are deployed as massive-scale distributed systems in the datacenter. Keeping data consistent and available despite server failures and concurrent updates is a formidable challenge. Two well-known abstractions, strongly consistent replication and serializable transactions, can free developers from these challenges by transparently masking failures and treating complex updates as atomic units. Yet the conventional wisdom is that these techniques are too expensive to deploy in high-performance systems. I will demonstrate a new approach to designing distributed systems that allows strongly consistent distributed systems to be built with little to no performance cost. Taking advantage of the properties and capabilities of the datacenter environment, we can co-design distributed protocols and the network layer. Specifically, I will describe two systems for state machine replication, Speculative Paxos and Network-Ordered Paxos, and one for distributed transaction processing, Eris, built using this approach. They are able to achieve 5-17x performance improvements over conventional designs. Moreover, they achieve performance within 2% of their weakly consistent alternatives, demonstrating that strong consistency and high performance are not incompatible. Dan Ports is Research Assistant Professor in Computer Science and Engineering at the University of Washington, where he leads the distributed systems research group. His group's research focuses on building practical distributed systems with strong theoretical underpinnings. Prior to joining the faculty at UW in 2015, Dan received the Ph.D. from MIT (2012), where he was advised by Barbara Liskov, and completed a postdoc at UW CSE. His research has been recognized with best paper awards at NSDI and OSDI.

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Colloquium Speaker: Dorsa Sadigh, Today- 4:30pm
by Nicole E. Wagenblast 28 Feb '17

28 Feb '17

MAE, COS, and ELE Colloquium Speaker Dorsa Sadigh , University of California, Berkeley Tuesday, February 28 - 4:30pm Computer Science 105 CS Host: Tom Funkhouser Towards a Theory of Safe and Interactive Autonomy Today’s society is rapidly advancing towards cyber-physical systems (CPS) that interact and collaborate with humans, e.g., semi-autonomous vehicles interacting with drivers and pedestrians, medical robots used in collaboration with doctors, or service robots interacting with their users in smart homes. The safety-critical nature of these systems requires us to provide provably correct guarantees about their performance in interaction with humans. The goal of my research is to enable such human-cyber-physical systems (h-CPS) to be safe and interactive. I aim to develop a formalism for design of algorithms and mathematical models that facilitate correct-by-construction control for safe and interactive autonomy. In this talk, I will first discuss interactive autonomy, where we use algorithmic human-robot interaction to be mindful of the effects of autonomous systems on humans, and further leverage these effects for better safety, efficiency, coordination, and estimation. I will then talk about safe autonomy, where we provide correctness guarantees, while taking into account the uncertainty arising from the environment. Further, I will discuss a diagnosis and repair algorithm for systematic transfer of control to the human in unrealizable settings. While the algorithms and techniques introduced can be applied to many h-CPS applications, in this talk, I will focus on the implications of my work for semi-autonomous driving. Dorsa Sadigh is a Ph.D. candidate in the Electrical Engineering and Computer Sciences department at UC Berkeley. Her research interests lie in the intersection of control theory, formal methods, and human-robot interactions. Specifically, she works on developing a unifying framework for safe and interactive autonomy. Dorsa received her B.S. from Berkeley EECS in 2012. She was awarded the NDSEG and NSF graduate research fellowships in 2013. She was the recipient of the 2016 Leon O. Chua department award and the 2011 Arthur M. Hopkin department award for achievement in the field of nonlinear science, and she received the Google Anita Borg Scholarship in 2016.

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Colloquium Speaker: Dorsa Sadigh, Tuesday, February 28- 4:30pm- reminder
by Nicole E. Wagenblast 27 Feb '17

27 Feb '17

MAE, COS, and ELE Colloquium Speaker Dorsa Sadigh , University of California, Berkeley Tuesday, February 28 - 4:30pm Computer Science 105 CS Host: Tom Funkhouser Towards a Theory of Safe and Interactive Autonomy Today’s society is rapidly advancing towards cyber-physical systems (CPS) that interact and collaborate with humans, e.g., semi-autonomous vehicles interacting with drivers and pedestrians, medical robots used in collaboration with doctors, or service robots interacting with their users in smart homes. The safety-critical nature of these systems requires us to provide provably correct guarantees about their performance in interaction with humans. The goal of my research is to enable such human-cyber-physical systems (h-CPS) to be safe and interactive. I aim to develop a formalism for design of algorithms and mathematical models that facilitate correct-by-construction control for safe and interactive autonomy. In this talk, I will first discuss interactive autonomy, where we use algorithmic human-robot interaction to be mindful of the effects of autonomous systems on humans, and further leverage these effects for better safety, efficiency, coordination, and estimation. I will then talk about safe autonomy, where we provide correctness guarantees, while taking into account the uncertainty arising from the environment. Further, I will discuss a diagnosis and repair algorithm for systematic transfer of control to the human in unrealizable settings. While the algorithms and techniques introduced can be applied to many h-CPS applications, in this talk, I will focus on the implications of my work for semi-autonomous driving. Dorsa Sadigh is a Ph.D. candidate in the Electrical Engineering and Computer Sciences department at UC Berkeley. Her research interests lie in the intersection of control theory, formal methods, and human-robot interactions. Specifically, she works on developing a unifying framework for safe and interactive autonomy. Dorsa received her B.S. from Berkeley EECS in 2012. She was awarded the NDSEG and NSF graduate research fellowships in 2013. She was the recipient of the 2016 Leon O. Chua department award and the 2011 Arthur M. Hopkin department award for achievement in the field of nonlinear science, and she received the Google Anita Borg Scholarship in 2016.

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Colloquium Speaker: Wyatt Lloyd, Today- 12:30pm
by Nicole E. Wagenblast 27 Feb '17

27 Feb '17

Colloquium Speaker Prof. Wyatt Lloyd, University of Southern California Monday, February 27- 12:30pm Computer Science 105 Low Latency and Strong Guarantees for Scalable Storage Scalable storage systems, where data is sharded across many machines, are necessary to support web services whose data is too large for a single machine to handle. An ideal system would provide the lowest latency—to make the web services built on top of it fast—and the strongest guarantees—to make programming the web service easier. Theoretical results prove that such an ideal system is impossible, but all hope is not lost! Our work has made progress on this problem from both directions: providing stronger guarantees for low latency systems and providing lower latency for systems with strong guarantees. I will cover one of these systems, Rococo, in detail. I will also touch on our recent impossibility result, the SNOW Theorem, and how it guided us in building new systems with latency-optimal read-only transactions. Wyatt Lloyd is a third-year Assistant Professor of Computer Science at the University of Southern California. His research interests include the theory, design, implementation, evaluation, and deployment of large-scale distributed systems. He received his Ph.D. from Princeton University in 2013 for the COPS and Eiger systems, which demonstrated stronger semantics were compatible with low latency for scalable geo-replicated storage. He then spent a year as a Postdoctoral Researcher at Facebook, and he continues to collaborate with its engineers on projects related to media processing, storage, and delivery.

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Colloquium Speaker: Wyatt Lloyd, Monday, February 27- 12:30pm- reminder
by Nicole E. Wagenblast 26 Feb '17

26 Feb '17

Colloquium Speaker Prof. Wyatt Lloyd, University of Southern California Monday, February 27- 12:30pm Computer Science 105 Low Latency and Strong Guarantees for Scalable Storage Scalable storage systems, where data is sharded across many machines, are necessary to support web services whose data is too large for a single machine to handle. An ideal system would provide the lowest latency—to make the web services built on top of it fast—and the strongest guarantees—to make programming the web service easier. Theoretical results prove that such an ideal system is impossible, but all hope is not lost! Our work has made progress on this problem from both directions: providing stronger guarantees for low latency systems and providing lower latency for systems with strong guarantees. I will cover one of these systems, Rococo, in detail. I will also touch on our recent impossibility result, the SNOW Theorem, and how it guided us in building new systems with latency-optimal read-only transactions. Wyatt Lloyd is a third-year Assistant Professor of Computer Science at the University of Southern California. His research interests include the theory, design, implementation, evaluation, and deployment of large-scale distributed systems. He received his Ph.D. from Princeton University in 2013 for the COPS and Eiger systems, which demonstrated stronger semantics were compatible with low latency for scalable geo-replicated storage. He then spent a year as a Postdoctoral Researcher at Facebook, and he continues to collaborate with its engineers on projects related to media processing, storage, and delivery.

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Colloquium Speaker: Asaf Cidon, Friday, March 3 - 12:30pm
by Nicole E. Wagenblast 25 Feb '17

25 Feb '17

Colloquium Speaker Asaf Cidon, Stanford University Friday, March 3 - 12:30pm Computer Science 105 Host: Prof. Kyle Jamieson Reliability and Performance Challenges at Cloud Scale Cloud computing is quickly becoming the backbone for critical societal applications, such as self-driving cars, tele-medicine and Internet of Things. However, the unprecedented scale of cloud infrastructure, with millions of servers spread across hundreds of data centers, introduces new fundamental challenges that were not faced by past computer systems. In my talk, I will present two examples of systems, Copysets and Cliffhanger, which leverage an analytical approach to tackle novel challenges introduced by the scale of the cloud. In Copysets, I present a novel replication framework that reduces the probability of data loss by over 10,000 times for the common scenario of simultaneous server failures. In Cliffhanger, I present a key-value cache that dynamically adapts to changing cloud application workloads, which reduces the number of misses by 35% or more. Both of these systems provide an example for my research approach, of building practical systems that tackle novel unstudied problems introduced by the scale of the cloud. Asaf Cidon is the Vice President, Content Security Services at Barracuda Networks. He currently also leads the cloud caching research project at Stanford. Asaf completed his PhD at Stanford under Mendel Rosenblum and Sachin Katti. His research on cloud and mobile systems was published in NSDI and Sigcomm, and received the Best Student Paper Award in Usenix ATC. Asaf was also the founder and CEO of Sookasa, a cloud storage security startup, which was acquired by Barracuda Networks. His research focuses on how to provide reliability and performance guarantees in large-scale cloud environments, and was adopted by several companies, including Facebook, NetApp, and Chartbeat.

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