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ASSET Seminar: Machine Learning: A Data-Centric Perspective, Aleksander Madry (Massachusetts Institute of Technology)

ABSTRACT: The training data that modern machine learning models ingest has a major impact on these models’ performance (as well as failures). Yet, this impact tends to be neither fully […]

ASSET Seminar: Lockout: Sparse Regularization of Neural Networks, Gilmer Valdes (UCSF)

ABSTRACT: Many regression and classification procedures fit a function f(x;w) of predictor variables x to data 〖{x_i,y_i}〗_1^N based on some loss criterion L(y,f(x;w)). Often, regularization is applied to improve accuracy […]

ASSET Seminar: Neurosymbolic Programming for Science, Swarat Chaudhuri (University of Texas at Austin)

PRESENTATION ABSTRACT: Neurosymbolic programming (NSP) is an emerging area of computing that bridges the fields of deep learning and program synthesis. Like in classical machine learning, the goal here is to […]

ASSET Seminar: , Dinesh Jayaraman (University of Pennsylvania)

ABSTRACT: An important goal of the field sensorimotor robot learning is to do away with cumbersome expertise-intensive task specification, so that general-purpose robots of the future might learn large numbers […]

ASSET Seminar: Decision-Aware Learning for Global Health Supply Chains, Osbert Bastani (University of Pennsylvania)

Abstract: Machine learning algorithms are increasingly used in conjunction with optimization to guide decision making. A key challenge is aligning the machine learning loss with the decision-making loss. Existing solutions […]

ASSET Seminar: Using Large Language Models to Build Explainable Classifiers, Chris Callison-Burch (University of Pennsylvania)

ABSTRACT: I’ll present research on using large language models (LLMs) to build explainable classifiers.   I will show off work from my PhD students and collaborators on several recent research […]

ASSET Seminar: The marriage of logic and learning: will it be a happily ever after?, Jyotirmoy Deshmukh (University of Southern California)

Presentation Abstract: Huge strides have made in the widespread adoption of autonomous and human-in-the-loop cyber-physical systems (CPS), partly fueled by dramatic improvements in learning-based techniques. An important aspect of such […]

ASSET Seminar: What makes learning to control easy or hard?, Nikolai Matni (University of Pennsylvania)

Presentation Abstract: Designing autonomous systems that are simultaneously high-performing, adaptive, and provably safe remains an open problem.  In this talk, we will argue that in order to meet this goal, […]

ASSET Seminar: Domain Adaptation Under Causally Structured Distribution Shifts, Zachary Lipton (Carnegie Mellon University)

Presentation Abstract: Faced with unlabeled data in deployment that is sampled from a different distribution than that which generated the training data, all bets are off. Moreover, while numerous heuristics […]

ASSET Seminar: Computational Social Listening for Public Health (Sharath Guntuku, University of Pennsylvania)

ABSTRACT: How can A.I.-based methods inform social listening applications during public health crises? The COVID-19 pandemic has uprooted the mode and method of human communication and interaction. The magnitude of […]

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