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— A key step in many statistical learning methods used in machine learning involves solving a convex optimization problem containing one or more hyper-parameters that must be sel...
Kristin P. Bennett, Jing Hu, Xiaoyun Ji, Gautam Ku...
The rise of convex programming has changed the face of many research fields in recent years, machine learning being one of the ones that benefitted the most. A very recent develop...
Reinforcement learning problems are commonly tackled with temporal difference methods, which use dynamic programming and statistical sampling to estimate the long-term value of ta...
The "schooling industry" is faced with an inescapable demand to redefine its endeavors in terms of producing learning, rather than providing instructions. We propose a h...