IFML Seminar
IFML Seminar: 05/02/25 - A New Paradigm for Learning with Distribution Shift
Abstract: We revisit the fundamental problem of learning with distribution shift, where a learner is given labeled samples from training distribution D, unlabeled samples from test distribution D′ and is asked to output a...
Upcoming Events
- May212:15 - 1:15pm
IFML Seminar
Event DetailsAbstract: We revisit the fundamental problem of learning with distribution shift, where a learner is given labeled samples from training...
Past Events
- February712:15 - 1:15pm
IFML Seminar
Event DetailsAbstract: 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
Event DetailsAbstract: 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
Event DetailsAbstract: Deep neural networks (DNNs) have become popular tools to solve ill-posed image recovery problems, such as those associated with...
- December101:30 - 4 pmEvent Details
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
Event DetailsAbstract: Computer vision has made remarkable advances through data-driven learning of image-text associations. Large-scale vision and language models like…
- December45:30 - 8 pm
Public Lecture
Event DetailsPublic event hosted by IBM, the Austin AI Alliance, and the Global AI Alliance (co-founded by IBM). Our Deep Proteins...
