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ASSET Seminar: “Poison and Cure: Non-Convex Optimization Techniques for Private Synthetic Data and Reconstruction Attacks”

Abstract: I will survey recent results describing the application of modern non-convex optimization methods to the problems of reconstruction attacks on private datasets (the “poison”), and the algorithmic generation of […]

ASSET/IBI Symposium

To learn more about the symposium, check out the page!

ASSET Seminar: “Efficient Sharing of AI Infrastructures with Specialized Serverless Computing”

Abstract: The efficient sharing of AI infrastructures is becoming increasingly important in both public and private data centers. This demand is driven by two key factors: the proliferation of specialized […]

ASSET Seminar: Işil Dillig (University of Texas at Austin)

ASSET Seminar: Matt Frederickson (Carnegie Mellon University)

ASSET Seminar: Virginia Smith (Carnegie Mellon University)

ASSET Seminar: “Towards Improving the Reliability of AI: Perspectives from Uncertainty Quantification and Fairness”

Abstract: Artificial intelligence holds enormous promise to automate our life. At the same time, AI systems can be incredibly brittle, unreliable, and biased. In this talk, I will present a few […]

ASSET Seminar: “Curious Embeddings, Hazy Oracles, and the Path to Safe, Cooperative AI”

Abstract: Cooperation through safe and trustworthy communication and interaction is fundamental to how human teams accomplish complex tasks. Yet, despite significant–and sometimes revolutionary–advances in AI, we have barely begun to […]

ASSET & Warren Center Research Mixer

The ASSET and Warren Center will be hosting a research mixer to welcome new PhD students and expose new and current students to the wide range of research in Penn […]

ASSET Seminar: “Towards Sustainable Artificial Intelligence and Datacenters”

Abstract: As the impact of artificial intelligence (AI) continues to proliferate, computer architects must assess and mitigate its environmental impact. This talk will survey strategies for reducing the carbon footprint […]

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