Video analytics applications use edge compute servers for processing videos. Compressed
models that are deployed on the edge servers for inference suffer from data drift where the …

As deep reinforcement learning (RL) showcases its strengths in networking, its pitfalls are
also coming to the public's attention. Training on a wide range of network environments leads …

With more videos being recorded by edge sensors (cameras) and analyzed by computer-vision
deep neural nets (DNNs), a new breed of video streaming systems has emerged, with …

Edge video analytics is becoming the solution to many safety and management tasks. Its
wide deployment, however, must first address the tension between inference accuracy and …

Traditional machine learning approaches for recognizing modes of transportation rely
heavily on hand-crafted feature extraction methods which require domain knowledge. So, we …

Deep reinforcement learning (RL) based rate adaptation has been popular in the past few
years. Unlike the handcrafted rate adaptation which requires manual effort from network …

This paper presents new results on a novel coupled-physics modality called magneto-acousto-electrical
tomography (MAET). With static magnetic field, a beam of ultrasound is applied …

Because of reinforcement learning's (RL) ability to automatically create more adaptive controlling
logics beyond the hand-crafted heuristics, numerous effort has been made to apply RL …

As deep reinforcement learning (RL) showcases its strengths in networking and systems, its
pitfalls also come to the public's attention--when trained to handle a wide range of network …

We describe a novel bioflocculant, MBF-15, which is an exopolysaccharide extracted from
the alkaliphilic bacterium Paenibacillus jamilae. The biophysical characteristics of MBF-15 …