How much data is sufficient to learn high-performing algorithms? Generalization guarantees for data-driven algorithm design
11:50 AM to 1:00 PM
Join Zoom Meeting https://columbiauniversity.zoom.us/j/94877990440?pwd= QWtWVGFBUTFTbHB2ak1mbmN3Mnd3QT09
Ellen Vitercik, Carnegie Mellon University
Algorithms often have tunable parameters that impact runtime and solution quality. For many algorithms used in practice, no parameter setting admits a meaningful worst-case guarantee, so the parameters are explicitly made available for the user to tune. Alternatively, the parameters may be tuned implicitly within the proof of a worst-case approximation ratio or runtime bound. Worst-case instances, however, may be rare or nonexistent in practice. A growing body of research has demonstrated that data-driven algorithm design can lead to significant gains in runtime and solution quality. Data-driven algorithm design uses a training set of problem instances sampled from an unknown, application-specific distribution and returns a parameter setting with strong average performance on the training set. We provide a broadly applicable theory for deriving generalization guarantees for data-driven algorithm design, which bound the difference between the algorithm's expected performance and its average performance over the training set. The challenge is that for many combinatorial algorithms, performance is a volatile function of the parameters: slightly perturbing the parameters can cause a cascade of changes in the algorithm’s behavior. Prior research has proved generalization bounds by employing case-by-case analyses of parameterized greedy algorithms, clustering algorithms, integer programming algorithms, and selling mechanisms. We uncover a unifying structure which we use to prove extremely general guarantees, yet we recover the bounds from prior research. Our guarantees apply whenever an algorithm's performance is a piecewise-constant, -linear, or—more generally—piecewise-structured function of its parameters. As we demonstrate, our theory also implies novel bounds for dynamic programming algorithms used in computational biology.
This talk is based on joint work with Nina Balcan, Dan DeBlasio, Travis Dick, Carl Kingsford, and Tuomas Sandholm.
Add to GMail
Thin Film Sensors + IoT as Enabling Technologies for Persistent Monitoring
1:00 PM to 2:00 PM
Register here - https://columbiauniversity.zoom.us/meeting/register/tJEqceCuqT0rEtP6DAJyNPGLrmJesOy_rCL7
John Kymissis, Columbia University
Energy-efficient miniature sensors based on thin-film technologies have transformed the ability to add sensing functionalities to a number of embedded applications. Combining these sensors with short and long-range wireless technologies offers the potential to offer persistent monitoring of otherwise invisible parameters, transforming the information available about a variety of natural and engineered environments. At Columbia, our group has been developing miniature sensors including microphones, photodetectors, spectrometers, and chemical sensors which meet the size and power requirements for embedded and IoT applications. Applications that will be discussed include the application of such systems on building energy efficiency, agricultural applications including soil and light measurement, and tracking and physiological monitoring of wild and laboratory animals.
Host: Debasis Mitra
Computer Science and Law: Opportunities and Research Directions
11:40 AM to 12:40 PM
Join Zoom Meeting https://columbiauniversity.zoom.us/j/94209356702?pwd=RXJOemUyOThycURuM0Roams4Ymw5dz09 Meeting ID: 942 0935 6702 Passcode: 892902
Joan Feigenbaum, Yale
Computer scientists have often treated law as though it can be reduced purely to a finite set of rules about which the only meaningful computational questions are those of decidability and complexity. Similarly, legislators and policy makers have often advocated general, imprecisely defined requirements and assumed that the tech industry could solve whatever technical problems arose in the design and implementation of products and services that conform to those requirements. The research area of Computer Science and Law seeks to replace these flawed, disciplinary approaches with a multidisciplinary focus on co-development of computing techniques, laws, and public policies. This talk will present ongoing efforts and open problems in this emerging area.
Data Orchestration is the New Compute: Computer Architecture for the Post-Moore Era
11:40 AM to 12:40 PM
Join Zoom Meeting https://columbiauniversity.zoom.us/j/99067271878?pwd=YWZhY2FJYWFwaEpvd1RFNFM3M2RFZz09 Meeting ID: 990 6727 1878 Passcode: 327099
Joel Emer, NVIDIA/MIT
Recent history is replete with myriad examples of new applications that have changed the course of computing and the world. These include the spreadsheet, visual editing, graphics, networking, and many more. Behind each of these advances were programs developed on easily-programmable and ever-faster processors. Unfortunately, as is widely acknowledged, the technological trend articulated by Moore's Law, which contributed significantly to creating the "ever faster" part of that recipe, is dead (or at least slowing significantly). However, as outlined in our "Science" article, "There's plenty of room at the top", there is promise in continuing Moore's Law-like improvements through a multi-pronged approach that includes software performance engineering, algorithm improvements, and hardware architecture advances. Among those researchers focusing on the hardware architecture advances prong, there are many who advocate significant specialization of the hardware to specific domains, which will typically be well-understood and of widely-acknowledged importance. This approach, however, is likely to impede the development of the next big application because there will be no generally-programmable platform on which to develop it. Therefore, I believe that the biggest challenge in evolving hardware architectures in the post-Moore era lies in striking the right balance between preserving broad programmability and enhancing efficiency. In this talk, I will discuss how we have approached that challenge by focusing on the aspects of the hardware that gives the most leverage to improve efficiency and by providing an abstraction that make it possible to compile to the new hardware. More specifically, since data movement has become the dominant consumer of energy, I will describe structures that facilitate "data orchestration" that reduce and optimize data movement. I also will describe abstractions that are intended to made it possible to compile high-level programs to these new hardware structures.
CS@CU MS Bridge Info Session
2:00 PM to 3:00 PM
Online Event
Prof. Tony Dear
Join Zoom Meeting
https://columbiauniversity.zoom.us/j/91105165256
Meeting ID: 911 0516 5256
One tap mobile
+16468769923,,91105165256# US (New York)
+13017158592,,91105165256# US (Germantown)
Dial by your location
+1 646 876 9923 US (New York)
+1 301 715 8592 US (Germantown)
+1 312 626 6799 US (Chicago)
+1 346 248 7799 US (Houston)
+1 669 900 6833 US (San Jose)
+1 253 215 8782 US (Tacoma)
Meeting ID: 911 0516 5256
Find your local number: https://columbiauniversity.zoom.us/u/aegS8k6m2s
Join by SIP
91105165256@zoomcrc.com
Join by H.323
162.255.37.11 (US West)
162.255.36.11 (US East)
221.122.88.195 (China)
115.114.131.7 (India Mumbai)
115.114.115.7 (India Hyderabad)
213.19.144.110 (EMEA)
103.122.166.55 (Australia)
209.9.211.110 (Hong Kong SAR)
64.211.144.160 (Brazil)
69.174.57.160 (Canada)
207.226.132.110 (Japan)
Meeting ID: 911 0516 5256
CS@CU MS Bridge Info Session
3:00 PM to 4:00 PM
Online Event
Prof. Tony Dear, https://www.cs.columbia.edu/ms-bridge/
Join Zoom Meeting
https://columbiauniversity.zoom.us/j/91307629351
Meeting ID: 913 0762 9351
One tap mobile
+16468769923,,91307629351# US (New York)
+13126266799,,91307629351# US (Chicago)
Dial by your location
+1 646 876 9923 US (New York)
+1 312 626 6799 US (Chicago)
+1 301 715 8592 US (Germantown)
+1 669 900 6833 US (San Jose)
+1 253 215 8782 US (Tacoma)
+1 346 248 7799 US (Houston)
Meeting ID: 913 0762 9351
Find your local number: https://columbiauniversity.zoom.us/u/abZsMh05wm
Join by SIP
91307629351@zoomcrc.com
Join by H.323
162.255.37.11 (US West)
162.255.36.11 (US East)
221.122.88.195 (China)
115.114.131.7 (India Mumbai)
115.114.115.7 (India Hyderabad)
213.19.144.110 (EMEA)
103.122.166.55 (Australia)
209.9.211.110 (Hong Kong SAR)
64.211.144.160 (Brazil)
69.174.57.160 (Canada)
207.226.132.110 (Japan)
Meeting ID: 913 0762 9351
Rising Stars in Engineering in Health - Virtual Workshop
9:00 AM to 5:00 PM
The emergent concept of managing health and wellness in a highly precise and personalized manner, both on an individual basis and for the larger population, increases the need for engineering advances that can improve human health. As technological developments allow us to take a more customized, holistic snapshot of the patient, the relationship between engineering and health science becomes increasingly symbiotic. At Columbia University, the Fu Foundation School of Engineering and Applied Science (FF SEAS) and the Vagelos College of Physicians and Surgeons (VP&S) work side-by-side to innovate at the intersection of engineering and health science and educate the next generation of scientists. As we pursue excellence in engineering in health, we have made it our priority to do so in an environment that embraces diversity, equity, and inclusion. With this in mind, FF SEAS and VP&S are pleased to present our inaugural Rising Stars in Engineering in Health Workshop. We welcome applicants who are interested in the intersection of engineering and biomedicine, and who include postdoctoral fellows/research scientists and graduate students who are 1-2 years away from applying for a faculty position. We especially encourage applicants from groups historically underrepresented in the disciplines. This full-day virtual workshop will take place on Friday, December 18, 2020, and will feature rapid-fire research talks, educational presentations, and panel discussions with Columbia Engineering and Medicine faculty.
Eligibility:
Applicants must be doctoral students, postdoctoral fellows, or research scientists who aspire to seek a faculty position in the interdisciplinary field of engineering and biomedicine in Fall 2021 or later.
Selection:
Twenty rising stars will be selected from the applicant pool to participate as presenters and participants in the Workshop. All qualified applicants, whether they are selected as a rising star or not, will be invited to attend the educational portions of the Workshop.
Application Requirements:
Applicants should submit the following materials via the Google Form above:
* 2-page academic statement
* 1-page diversity statement
* CV
Applicants are encouraged to submit their application as soon as possible and no later than November 30, 2020.
Notification:
Successful applicants will be notified by December 7, 2020.
Workshop Sample Schedule:
• Welcome and Introduction (Deans of Engineering and Medicine)
• Senior Faculty Panel: Why Academics?
• How to Prepare Academic and Diversity Statements
• How to Give an Efficient Job Talk and Chalk Talk
• Junior Faculty Panel: Pearls and Pitfalls in Academic Job Applications
• Rapid-Fire Research Presentations
Apply here - https://docs.google.com/forms/d/e/1FAIpQLSe1sXvppU9HKpG-zOQOzRMw9i6LQ7z_-i4MHhg3Ro_v_qilQg/viewform
Event Contact Information:
Alexis Newman
alexis.newman@columbia.edu
Add to GMail