IFML Seminar
IFML Seminar: 10/17/25 - Sample-Efficient Personalized Reward Models for Pluralistic Alignment
Abstract: Large pre-trained models trained on internet-scale data are often not ready for deployment out-of-the-box. They are heavily fine-tuned and aligned using large quantities of human preference data, usually elicited using pairwise comparisons. While...
Upcoming Events
- October1712:15 - 1:15pm
IFML Seminar
Event DetailsAbstract: Large pre-trained models trained on internet-scale data are often not ready for deployment out-of-the-box. They are heavily fine-tuned and...
- October2412:15 - 1:15pm
IFML Seminar
Event DetailsAbstract: Learning from sequential, temporally-correlated data is a core facet of modern machine learning and statistical modeling. Yet our fundamental...
- November712:15 - 1:15pm
IFML Seminar
Event DetailsAbstract: Retraining a model using its own predictions together with the original, potentially noisy labels is a well-known strategy for...
Past Events
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IFML Seminar
Event DetailsAbstract: I will present a polynomial time algorithm to recover planted cliques in the semi random models introduced by Feige...
- March712:15 - 1:15pm
IFML Seminar
Event DetailsAbstract: In the first part of this presentation, I'll present a non-asymptotic bound for the spectral norm of a Gaussian...
- March4throughMarch6
Public Lecture
Event DetailsJoin us for the 2025 AI + Robotics Research Symposium -- three days of talks, panels, presentations, and networking opportunities...
- February2812:15 - 1:15pm
IFML Seminar
Event DetailsAbstract: Learning representations that generalize across diverse downstream tasks is a fundamental challenge in machine learning. Contrastive learning, self…
- February20throughFebruary21
Workshop
Event Details2 days of academic research presentations on the mathematical theory underpinning modern machine learning paradigms. Presented by The University of...
- February1412:15 - 1:15pm
IFML Seminar
Event DetailsAbstract: Mainstream artificial neural network models, such as Deep Neural Networks (DNNs) are computation-heavy and energy-hungry. Weightless Neural…
