Universal Source Coding for Monotonic and Fast Decaying Monotonic Distributions von Shamir, Gil I.

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Sequential universal modeling for non-binary sequences with constrained distributions von Drmota, Michael, Shamir, Gil I., Szpankowski, Wojciech

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Universal Lossless Compression With Unknown Alphabets-The Average Case von Shamir, G.I.

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On the MDL principle for i.i.d. sources with large alphabets von Shamir, G.I.

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Entropy of Patterns of i.i.d. Sequences-Part I: General Bounds von Shamir, G.I.

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Universal source controlled channel decoding with nonsystematic quick-look-in turbo codes von Shamir, G., Kai Xie

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Low-complexity sequential lossless coding for piecewise-stationary memoryless sources von Shamir, G.I., Merhav, N.

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Sufficiently Informative and Relevant Features: An Information-Theoretic and Fourier-Based Characterization von Heidari, Mohsen, Sreedharan, Jithin K., Shamir, Gil, Szpankowski, Wojciech

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Universal Context Based Decoding with Low-Density Parity-Check Codes von Li Wang, Shamir, G.I.

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Universal lossless source controlled channel decoding for i.i.d. sequences von Shamir, G.I., Xie, K.

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Asymptotically optimal low-complexity sequential lossless coding for piecewise-stationary memoryless sources--Part I: The regular case von Shamir, Gil I, Costello, Daniel J

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Universal lossless coding for sources with repeating statistics von Shamir, G.I., Costello, D.J.

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LISTWISE LEARNING TO RANK von SHAMIR, Gil

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Minimum deep learning with gating multiplier von Shamir, Gil

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LEARNING TO RANK VIA UNIVARIATE ORDINAL REGRESSION von SHAMIR, Gil

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LEARNING TO RANK WITH ORDINAL REGRESSION GUIDED WITH CONDITIONAL PROBABILITIES von SHAMIR, Gil

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Forecasting Uncertainty in Machine Learning Models von Shamir, Gil

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LEARNING TO RANK WITH ORDINAL REGRESSION von SHAMIR, Gil

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MULTI-LABEL PAIRWISE RANKING von SHAMIR, Gil

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Minimum Deep Learning with Gating Multiplier von Shamir, Gil

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