Title: Collaborative Regression and Classification via Bootstrapping Abstract: In modern machine learning problems and applications, the data that we are dealing with have large dimensions as well as amount, making data analysis time-consuming and computationally[...]

Title: Brain structure segmentation using multiple MRI pulse sequences Abstract: Medical image segmentation is the process of delineating anatomical structures of interest in images. Automatic segmentation algorithms applied to brain magnetic resonance images (MRI) allow for[...]

Title: Minimally-Invasive Lens-free Computational Microendoscopy Abstract: Ultra-miniaturized imaging tools are vital for numerous biomedical applications. Such minimally invasive imagers allow for navigation into hard-toreach regions and, for example, observation of deep brain activity in freely moving animals[...]

Title: Semi-supervised training for automatic speech recognition. Abstract: State-of-the-art automatic speech recognition (ASR) systems use sequence-level objectives like Connectionist Temporal Classification (CTC) and Lattice-free Maximum Mutual Information (LF-MMI) for training neural network-based acoustic models. These[...]

Title: Strategies for Handling Out-of-Vocabulary Words in  Automatic Speech Recognition Abstract: Nowadays, most ASR (automatic speech recognition) systems deployed in industry are closed-vocabulary systems, meaning we have a limited vocabulary of words the system can recognize,[...]