no code implementations • 30 Aug 2020 • Sheng-Chieh Lin, Ting-Wei Lin, Jing-Kai Lou, Ming-Feng Tsai, Chuan-Ju Wang
In this paper, we propose a two-stage ranking approach for recommending linear TV programs.
no code implementations • 10 Aug 2017 • Shang-Xuan Zou, Chun-Yen Chen, Jui-Lin Wu, Chun-Nan Chou, Chia-Chin Tsao, Kuan-Chieh Tung, Ting-Wei Lin, Cheng-Lung Sung, Edward Y. Chang
Scale of data and scale of computation infrastructures together enable the current deep learning renaissance.
no code implementations • NeurIPS 2014 • Ian En-Hsu Yen, Ting-Wei Lin, Shou-De Lin, Pradeep K. Ravikumar, Inderjit S. Dhillon
In this paper, we propose a Sparse Random Feature algorithm, which learns a sparse non-linear predictor by minimizing an $\ell_1$-regularized objective function over the Hilbert Space induced from kernel function.