Location: Zoom meeting: https://us02web.zoom.us/j/4685913265Title:Interactive Learning with Discriminative Feature Feedback  Abstract:In this talk I will discuss a model of learning with feature-based explanations, that we call Discriminative Feature Feedback. This model formalizes a natural notion of interactive learning with explanations. We study algorithms for this model, including robust algorithms for adversarial and stochastic settings, and derive insightful new results ... Read more

NameLab HeadTitle12:00-12:15Ori ErnstIdo DaganBeyond End-to-End: The Case of Multi Document Summarization12:15-12:30Shon OtmazginYoav GoldbergLingMess & F-COREF: Fast, Accurate, and Easy to Use models for Coreference Resolution12:30-12:45Lior Frenkel Jacob GCalibration of Medical Imaging Classification Systems with Weight Scaling12:45-13:00Coby PensoEthan FetayaFunctional Ensemble Distillation13:00-14:00Lunch

Location:Engineering building (1103), room 329Title:Notions of simplicity in deep learning: From time series to images Abstract:It is standard practice indeep learning to train large models on relatively small datasets. This canpotentially lead to severe overfitting, but more often than not, test error isactually good. This phenomenon has prompted research on the so-called "ImplicitBias of Deep Learning Algorithms". ... Read more

Location:Engineering building (1103), room 329Title:Exploring Deep Neural Collapse via Extended and Controlled Unconstrained Features ModelsAbstract:Training deep neural networks for classification often includes minimizing the training loss beyond the zero training error point. In this phase of training, a "neural collapse" (NC) behavior has been empirically observed: the variability of features (outputs of the penultimate layer) ... Read more