
IFML Seminar
IFML Seminar: 10/24/25 - Learning from Many Trajectories
Abstract: Learning from sequential, temporally-correlated data is a core facet of modern machine learning and statistical modeling. Yet our fundamental understanding of sequential learning remains incomplete, particularly in the multi-trajectory setting where data consists...
Upcoming Events
- October2412:15 - 1:15pm
IFML Seminar
Abstract: 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
Abstract: Retraining a model using its own predictions together with the original, potentially noisy labels is a well-known strategy for...
Past Events
- February1412:15 - 1:15pm
IFML Seminar
Abstract: Mainstream artificial neural network models, such as Deep Neural Networks (DNNs) are computation-heavy and energy-hungry. Weightless Neural…
- February712:15 - 1:15pm
IFML Seminar
Abstract: Reinforcement Learning from Human Feedback (RLHF) has become the predominant method for aligning large language models (LLMs) to be...
- January3112:15 - 1:15pm
IFML Seminar
Abstract: We pose a fundamental question in computational learning theory: can we efficiently test whether a training set satisfies the...
- December1312:15 - 1:15pm
IFML Seminar
Abstract: Deep neural networks (DNNs) have become popular tools to solve ill-posed image recovery problems, such as those associated with...
- December101:30 - 4 pm
One of the most striking findings in modern research on large language models (LLMs) is that, given a model and...
- December612:15 - 1:15pm
IFML Seminar
Abstract: Computer vision has made remarkable advances through data-driven learning of image-text associations. Large-scale vision and language models like…