Benjamin Tang

Title: Benjamin Tang and His Patent in Efficient LDPC Decoding.

Introduction

Benjamin Tang is an inventor based in New York, New York. His patent work concerns applying machine learning to improve the efficiency of iterative computations used in communications technology.

Latest Patents

The provided information identifies one patent associated with Tang: Deep Learning Optimized Iterative Process with Application to the Optimization of Layered Belief Propagation for Low Density Parity Check Decoding. The invention defines trainable parameters and differentiable gating functions, then uses a machine-learning-based optimization to select which iterations of a process should be performed. It jointly optimizes accuracy and the number of active iterations, and applies this approach to layered belief propagation for low-density parity-check (LDPC) decoding. The supplied data lists 1 patent for Tang.

Career Highlights

Tang is associated with Qualcomm Incorporated. His patent reflects work on reducing unnecessary computation while maintaining decoding accuracy, an approach relevant to efficient communications systems.

Collaborations

The provided information names Aaron Klein and Vincent Loncke as Tang’s coworkers. It does not specify their roles in the patent or whether they collaborated directly on the invention.

Conclusion

Benjamin Tang’s listed patent applies machine-learning optimization to streamline LDPC decoding by selecting an effective subset of iterations. It highlights his connection to Qualcomm Incorporated and innovation in efficient communications technology.