Much emphasis in multiagent reinforcement learning (MARL) research is placed on ensuring that MARL algorithms (eventually) converge to desirable equilibria. As in standard reinfor...
Traditionally, distributed computing problems have been solved by partitioning data into chunks able to be handled by commodity hardware. Such partitioning is not possible in case...
Many settings of unsupervised learning can be viewed as quantization problems — the minimization of the expected quantization error subject to some restrictions. This allows the ...
Alex J. Smola, Robert C. Williamson, Sebastian Mik...
Abstract. We present a unified and complete account of maximum entropy distribution estimation subject to constraints represented by convex potential functions or, alternatively, b...
Abstract. The Internet has instigated a critical need for automated tools that facilitate integrating countless databases. Since non-technical end users are often the ultimate repo...