Abstract: The explicit incorporation of task-specific inductive biases through symmetry has emerged as a crucial design precept in the development of high-performance machine learning models. Symmetry-aware neural networks, such as […]
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 […]
Abstract: Transformer-based language models have undoubtedly become the dominant and favorite architecture for language generation of our time. However, although they provide impressive text quality, they tend to be hard […]
Abstract: Modern machine learning methods are revolutionizing what we can do with data, from tiktok video recommendations to biomarkers discovery in cancer research. Yet, the complexity of these deep models […]
Abstract: Tumors are complex and heterogeneous systems, which challenge their classification and treatment. The Silverbush lab decodes tumor heterogeneity and plasticity to understand how cancer cells transform to become more […]
Abstract: Performance of control systems depend on the nature of available measurements. Perception of edges, keypoints, landmarks and other natural semantic features make certain coarse measurements available to control systems operating in […]
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 […]
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 […]
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 […]
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 […]
