I will discuss what I believe are the biggest insights in computer science
theory. They are not the obvious ones---at least not all are obvious. The
talk should be accessible to almost anyone. Although some experts may
disagree with my list of insights. I will also make an attempt to outline
what I see as the future of computer science theory: what will happen
in the next five, ten, and twenty years.
here is a brief bio for Dick Lipton.
I will discuss some open problems that I have worked on forever. I think these problems should be solvable but progress is very limited. The first is essentially the halting problem for linear automata. It has been called a shame that we cannot prove it is either decidable or not. I will report on some partial results. The other two problems I will leave as a surprise, but they are both related to our P vs NP question.
Abstract: An important constraint that algorithms must satisfy when analyzing sensitive data from individuals is privacy. Differential privacy has revolutionized the way we reason about privacy and has championed the need for data analysis algorithms with provable guarantees.
Can we speed up a CPU-bound server application that does complex in-memory processing under tight latency budget, by moving most of its in-memory state to Flash storage / SSD (which is ~500x slower than RAM) ? Can we achieve crash-tolerance via online process-pair replication and consistent virtual memory snapshotting in a CPU-bound system, while incurring negligible common-case performance hit? Can we speed up petabyte-scale “big data” query processing in a cluster by orders of magnitude while simultaneously reducing cost?
Bonfire is a fast growing, Madison-based, startup with two UW graduates a
part of our co-founding team. We have an opportunity that we are excited to
share with the UW Computer Science community. We are seeking an
undergraduate or graduate student or group of students who are proficient in
web/mobile application development. We are seeking students with
project can count as credit or be a freelance project.
Accelerate your career by joining a dynamic, successful team breaking new ground in
technology and trading. As a leader in the financial industry, we need incredibly talented
minds to develop the next generation of sophisticated, proprietary trading technology
as well as mission-critical applications supporting our other businesses – no experience
in financial markets required.
This is an exciting time in biomedical data science. It is now possible to collect substantial information about individuals and their encounters with health care. Our ultimate goal is to integrate this data, along with data and findings from those engaged in basic science, to identify new opportunities to improve health. Broad data sharing will further our progress towards this goal. However, data sharing poses both cultural and technological challenges.