Today's AI agents are a primitive approximation of what agents are meant to be. True agentic AI requires serious advances in reinforcement learning and complex memory.
First-order derivatives: n additional function calls are needed. Second-order derivatives based on gradient calls, when the "grd" module is specified (Dennis and Schnabel 1983): n additional gradient ...
Abstract: This paper proposes a novel Viterbi-Like successive cancellation (VL-SC) decoding algorithm for polar codes. The algorithm employs the bit log-likelihood-ratio as the “penalty value” within ...
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