Conditional Generative Adversarial Networks (cGANs) have enabled controllable image synthesis for many vision and graphics applications. However, recent cGANs are 1-2 orders of magnitude more compu…
In this article, we develop automated inference methods for “local” parameters in a collection of convexity constrained models based on the natural constrained tuning-free estimators. A canonic…
We propose the regularized linear programming discriminant (LPD) rule with folded concave penalty in the ultrahigh-dimensional regime. We use the local linear approximation (LLA) algorithm to redir…
In the present paper, we demonstrate the first outdoor free-space optical communication (FSOC) system with real-time video transmission in a 2-μm-band with a state-of-the-art data rate performance…
Tilted fiber Bragg grating (TFBG) sensors are widely used in biochemical and electrochemical sensing due to their high sensitivity to refractive index (RI) of the surrounding medium. Ability of TFB…
We demonstrate a high-energy and high-average power Mamyshev oscillator based on a high performance large-mode-area step-index germanosilicate-cladding Yb-doped fiber. The oscillation of higher-ord…
An approach to photonic generation of a windowed binary phase-coded microwave waveform with suppressed spectrum sidelobes is proposed and demonstrated. An optical double sideband plus carrier signa…
Dynamic neural network is an emerging research topic in deep learning. Compared to static models which have fixed computational graphs and parameters at the inference stage, dynamic networks can ad…
Weakly supervised temporal action localization aims at learning the instance-level action pattern from the video-level labels, where a significant challenge is action-context confusion. To overcome…
With substantial amount of time, resources and human (team) efforts invested to explore and develop successful deep neural networks (DNN), there emerges an urgent need to protect these inventions f…