Iteration complexity of randomized block-coordinate descent methods for minimizing a composite function von Richtarik, Peter, Takac, Martin

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Stochastic Reformulations of Linear Systems: Algorithms and Convergence Theory von Richtárik, Peter, Takáč, Martin

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Parallel coordinate descent methods for big data optimization von Richtarik, Peter, TakaAe, Martin

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MagBERT: Magnetics Knowledge Aware Language Model Coupled with a Question Answering Pipeline for Curie Temperature Extraction Task von Zhumabayeva, Aigerim, Ranjan, Nikhil, Takáč, Martin, Sanvito, Stefano, Ucar, Huseyin

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A Deep Q-Network for the Beer Game: Deep Reinforcement Learning for Inventory Optimization von Oroojlooyjadid, Afshin, Nazari, MohammadReza, Snyder, Lawrence V., Takáč, Martin

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Scaling Up Quasi-newton Algorithms: Communication Efficient Distributed SR1 von Jahani, Majid, Nazari, Mohammadreza, Rusakov, Sergey, Berahas, Albert S., Takáč, Martin

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DynNet: Physics-based neural architecture design for nonlinear structural response modeling and prediction von Sadeghi Eshkevari, Soheil, Takáč, Martin, Pakzad, Shamim N., Jahani, Majid

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Mini-Batch Semi-Stochastic Gradient Descent in the Proximal Setting von Konecny, Jakub, Liu, Jie, Richtarik, Peter, Takac, Martin

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Convolutional Neural Network Approach for Robust Structural Damage Detection and Localization von Gulgec, Nur Sila, Takáč, Martin, Pakzad, Shamim N

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Applying deep learning to the newsvendor problem von Oroojlooyjadid, Afshin, Snyder, Lawrence V., Takáč, Martin

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Modeling and Optimization: Theory and Applications: MOPTA, Bethlehem, PA, USA, August 2016 Selected Contributions

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Random-reshuffled SARAH does not need full gradient computations von Beznosikov, Aleksandr, Takáč, Martin

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Structural sensing with deep learning: Strain estimation from acceleration data for fatigue assessment von Gulgec, Nur Sila, Takáč, Martin, Pakzad, Shamim N.

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Randomized sketch descent methods for non-separable linearly constrained optimization von Necoara, Ion, Takac, Martin

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On optimal probabilities in stochastic coordinate descent methods von Richtárik, Peter, Takáč, Martin

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Dual Free Adaptive Minibatch SDCA for Empirical Risk Minimization von He, Xi, Tappenden, Rachael, Takáč, Martin

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Modal Identification of Bridges Using Mobile Sensors with Sparse Vibration Data von Sadeghi Eshkevari, Soheil, Pakzad, Shamim N, Takáč, Martin, Matarazzo, Thomas J

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Matrix completion under interval uncertainty von Mareček, Jakub, Richtárik, Peter, Takáč, Martin

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Stochastic Gradient Methods with Preconditioned Updates von Sadiev, Abdurakhmon, Beznosikov, Aleksandr, Almansoori, Abdulla Jasem, Kamzolov, Dmitry, Tappenden, Rachael, Takáč, Martin

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Reinforcement Learning Approach to Stochastic Vehicle Routing Problem with Correlated Demands von Iklassov, Zangir, Sobirov, Ikboljon, Solozabal, Ruben, Takac, Martin

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