Upcoming Seminars
Co-sponsored by the Department of Computer Science and the Department of Electrical and Computer Engineering
Users who wish to exercise privacy rights or make privacy choices must often rely on website or app user interfaces. However, too often, these user interfaces suffer from usability deficiencies ranging from being…
Speaker
Previous Seminars
Rose Yu is an assistant professor at the University of California San Diego, Department of Computer Science and Engineering. Her research focuses on advancing machine learning techniques for large-scale spatiotemporal data analysis, with applications to sustainability, health, and physical sciences.
Lunch available at 12:00 p.m. Please RSVP to [email protected]
Speaker
Co-sponsored by the Department of Computer Science and the Department of Electrical and Computer Engineering
The Arbitrum blockchain protocol started as a Princeton University research project, and has grown into a robust community hosting hundred of applications and over 600,000 monthly users. Along the way, the system has…
Speaker
Co-sponsored by the Department of Computer Science and the Department of Electrical and Computer Engineering
Details: TBA
Bio:
Alessandro Acquisti is the Trustees Professor of Information Technology and Public Policy at the Heinz College, Carnegie Mellon University…
Speaker
Please register here to attend in person.
Co-sponsored by the Department of Computer Science and the Department of Electrical and Computer Engineering
Computer security is traditionally about the protection of technology, whereas trust and safety…
Speaker
Please register here to attend in person.
Co-sponsored by the Department of Computer Science and the Department of Electrical and Computer Engineering
…Speaker
Abstract:
With the slowing of Moore's law, computer architects have turned to domain-specific hardware accelerators to improve the performance and efficiency of computing systems. However, programming these systems entails significant modifications to the software stack to properly leverage the specialized…
Speaker
Abstract:
Recent advances in machine learning such as deep learning have led to powerful tools for modeling complex data with high predictive accuracy.
However, the resulting models are typically black box, limiting their usefulness in scientific discovery. Here we show that an "interpretable-by-design''…
Speaker
Risk-averse optimization plays a major role in the design of safety for machine learning applications. In this talk, we will present a set of tools to enhance the robustness of models and algorithms to potentially harmful data shifts.
Lunch from 12:15 p.m., RSVP to [email protected]
Speaker
In the context of first-order algorithms subject to random gradient noise, we study the trade-offs between the convergence rate (which quantifies how fast the initial conditions are forgotten) and the "risk" of suboptimality, i.e., deviations from the expected suboptimality.
Lunch from 12:15 p.m., RSVP to [email protected]
Speaker
Sparse statistical estimators are increasingly prevalent due to their ease of interpretability and superior out-of-sample performance. However, sparse estimation problems with an L0 constraint, restricting the support of the estimators, are challenging (typically NP-hard, but not always) non-convex optimization problems.