Improving the sample efficiency of reinforcement learning algorithms to scale up to larger and more realistic domains is a current research challenge in machine learning. Model-ba...
Many metaheuristics have difficulty exploring their search space comprehensively. Exploration time and efficiency are highly dependent on the size and the ruggedness of the search...
The visualization and exploration of multivariate data is still a challenging task. Methods either try to visualize all variables simultaneously at each position using glyph-based ...
— Increasingly prominent variational effects impose imminent threat to the progress of VLSI technology. This work explores redundancy, which is a well-known fault tolerance techn...
Di Wu, Ganesh Venkataraman, Jiang Hu, Quiyang Li, ...
With the advent of online social networks, the trust-based approach to recommendation has emerged which exploits the trust network among users and makes recommendations based on t...
Samaneh Moghaddam, Mohsen Jamali, Martin Ester, Ja...