Search Results for author:
Found 5 papers, 3 papers with code
GloNets: Globally Connected Neural Networks
Deep learning architectures suffer from depth-related performance degradation, limiting the effective depth of neural networks.
Increasing biases can be more efficient than increasing weights
We introduce a novel computational unit for neural networks that features multiple biases, challenging the traditional perceptron structure.
Score vs. Winrate in Score-Based Games: which Reward for Reinforcement Learning?
In the last years, the DeepMind algorithm AlphaZero has become the state of the art to efficiently tackle perfect information two-player zero-sum games with a win/lose outcome.
SAI: a Sensible Artificial Intelligence that plays with handicap and targets high scores in 9x9 Go (extended version)
We develop a new model that can be applied to any perfect information two-player zero-sum game to target a high score, and thus a perfect play.
SAI, a Sensible Artificial Intelligence that plays Go
We propose a multiple-komi modification of the AlphaGo Zero/Leela Zero paradigm.
