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An Interpretable and Efficient Infinite-Order Vector Autoregressive Model for High-Dimensional Time Series
As a special infinite-order vector autoregressive (VAR) model, the vector autoregressive moving average (VARMA) model can capture much richer temporal patterns than the widely used finite-order VAR model.
A New Measure of Model Redundancy for Compressed Convolutional Neural Networks
While recently many designs have been proposed to improve the model efficiency of convolutional neural networks (CNNs) on a fixed resource budget, theoretical understanding of these designs is still conspicuously lacking.
Demo: iJam with Channel Randomization
Their secrecy rate (bit generation rate) depends heavily on the randomness of the channel, which may reduce significantly in a stable environment.
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