PRESENTATION 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 […]

PRESENTATION 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 […]

PRESENTATION 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 […]

PRESENTATION ABSTRACT  In this new era of deep learning, the emergent algorithmic reasoning capabilities of Transformer models have led to significant advancements in natural language processing, program synthesis, and theorem […]

Presentation Abstract: Scientific discoveries, fueled by data collected during the course of care, are promising to radically change how we think about health, disease, prevention and treatment. However, the very […]

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 […]