16 citations · 31 across the 3 of their papers we have counts for
4 papers
LNAS: Learning to Optimize Neural Architectures via Continuous-Action Reinforcement Learning
Keith G. Mills, Fred X. Han, Mohammad Salameh +6
Neural architecture search (NAS) has achieved remarkable results in deep neural network design. Differentiable architecture search converts the search over discrete architectures i…
Generative Adversarial Neural Architecture Search
Seyed Saeed Changiz Rezaei, Fred X. Han, Di Niu +5
Despite the empirical success of neural architecture search (NAS) in deep learning applications, the optimality, reproducibility and cost of NAS schemes remain hard to assess. In t…
Combinatorial Optimization by Decomposition on Hybrid CPU--non-CPU Solver Architectures
Ali Narimani, Seyed Saeed Changiz Rezaei, Arman Zaribafiyan
The advent of new special-purpose hardware such as FPGA or ASIC-based annealers and quantum processors has shown potential in solving certain families of complex combinatorial opti…
A New Achievable Rate for the Gaussian Parallel Relay Channel
Seyed Saeed, Changiz Rezaei, Shahab Oveis Gharan +1
Schein and Gallager introduced the Gaussian parallel relay channel in 2000. They proposed the Amplify-and-Forward (AF) and the Decode-and-Forward (DF) strategies for this channel.…