High-end networked applications such as distance visualization, distributed data analysis, and advanced collaborative environments have demanding quality of service (QoS) requirements. Particular challenges include concurrent flows with different QoS specifications, high bandwidth flows, application-level monitoring and control, and end-to-end QoS across networks and other devices. We describe ...

We propose an end-to-end distributionally robust system for portfolio construction that integrates the asset return prediction model with a optimization model. also show how to learn risk-tolerance parameter and degree of robustness directly from data. End-to-end systems have advantage in information can be communicated between decision layers during training, allowing parameters trained final ...

One-class classification (OCC) poses as an essential component in many machine learning and computer vision applications, including novelty, anomaly, outlier detection systems. With a known definition for target or normal set of data, one-class classifiers can determine if any given new sample spans within the distribution class. Solving this task general setting is particularly very challengin...

We present YORO - a multi-modal transformer encoder-only architecture for the Visual Grounding (VG) task. This task involves localizing, in an image, object referred via natural language. Unlike recent trend literature of using multi-stage approaches that sacrifice speed accuracy, seeks better trade-off between accuracy by embracing single-stage design, without CNN backbone. consumes language q...