PhD Thesis Defense
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PhD Thesis Defense
Benjamin Attal
Robust Inverse Rendering with Physics-Based Light Transport and Active Sensors
Abstract: Inverse rendering is the process of recovering the shape, materials, and lighting conditions of an environment from a set of images. Both this process as a whole and its individual components are fundamental to applications ranging from medical imaging to astronomy, and from AR/VR to embodied intelligence. In the thesis work discussed in this […]
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PhD Thesis Defense
Shuli Jiang
Communication Efficient and Differentially Private Optimization
Abstract: In modern machine learning, the abundance of data generated across diverse and distributed sources has made distributed training a central paradigm, particularly in large-scale applications such as Federated Learning. However, two key challenges arise in distributed training: ensuring communication efficiency and preserving the privacy of sensitive data used during training. This thesis addresses these […]
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PhD Thesis Defense
Saumya Saxena
Learning Generalizable Robot Skills for Dynamic and Interactive Tasks
Abstract: Recent years have seen growing interest in developing robots capable of lifelong reliable operation in human-centric environments. Despite impressive recent progress towards long-horizon tasks such as laundry folding, current efforts are predominantly focused on quasi-static tasks in structured settings. General-purpose assistive robots should be capable of performing a wider range of dynamic and dexterous […]