IDEAS/STAT Optimization Seminar: “Theoretical foundations for multi-agent learning”
As learning algorithms become increasingly capable of acting autonomously, it is important to better understand the behavior that results from their interactions. For example, a pervasive challenge in multi-agent learning […]
ASSET Seminar: “Controlling Language Models”
Abstract: Controlling language models is key to unlocking their full potential and making them useful for downstream tasks. Successfully deploying these models often requires both task-specific customization and rigorous auditing […]
MEAM Seminar: “Digital Twins for the Earth System”
Reliable forecasts of the Earth system are crucial for human progress and safety from natural disasters. Artificial intelligence offers substantial potential to improve prediction accuracy and computational efficiency in this […]
ASSET Seminar: “Beyond Scaling: Frontiers of Retrieval-Augmented Language Models”
Abstract: Large Language Models (LMs) have demonstrated remarkable capabilities by scaling up training data and model sizes. However, they continue to face critical challenges, including hallucinations and outdated knowledge, which […]
ASSET Seminar: “Demystifying the Inner Workings of Language Models”
Abstract: Large language models (LLMs) power a rapidly-growing and increasingly impactful suite of AI technologies. However, due to their scale and complexity, we lack a fundamental scientific understanding of much […]
ASSET Seminar: “Steering Machine Learning Ecosystems of Interacting Agents”
Abstract: Modern machine learning models—such as LLMs and recommender systems—interact with humans, companies, and other models in a broader ecosystem. However, these multi-agent interactions often induce unintended ecosystem-level outcomes such […]
ESE Spring Seminar – “AI as a Lens: Expanding Vision for Scientific Discovery”
Conventional approaches to scientific discovery often prioritize building larger sensors, gathering more data, and scaling up computational power. In this talk, I will present a complementary perspective: extracting insights hidden […]
ESE Spring Seminar – “Machine Learning: Algorithmic and Economic Perspectives”
Algorithms are increasingly integrated into various societal applications, often directly interacting with people and communities. This highlights the importance of understanding the interplay between algorithmic decisions and economic incentives when […]
ASSET Seminar: “From Data to Insights: Trustworthy Solutions for Imaging Problems”
Abstract: Extracting insights from imaging data used to be straightforward: every component of imaging systems was engineered by humans, the analysis and interpretation of the collected data was driven by […]
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 […]