Search Results - Hallak, Nadav

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  1. 1
    A Dynamic Alternating Direction of Multipliers for Nonconvex Minimization with Nonlinear Functional Equality Constraints

    A Dynamic Alternating Direction of Multipliers for Nonconvex Minimization with Nonlinear Functional Equality Constraints by Cohen, Eyal, Hallak, Nadav, Teboulle, Marc

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  2. 2
    Finding Second-Order Stationary Points in Constrained Minimization: A Feasible Direction Approach

    Finding Second-Order Stationary Points in Constrained Minimization: A Feasible Direction Approach by Hallak, Nadav, Teboulle, Marc

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  3. 3
    A Path-Based Approach to Constrained Sparse Optimization

    A Path-Based Approach to Constrained Sparse Optimization by Hallak, Nadav

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  4. 4
    Optimization problems involving group sparsity terms

    Optimization problems involving group sparsity terms by Beck, Amir, Hallak, Nadav

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  5. 5
    On the Convergence to Stationary Points of Deterministic and Randomized Feasible Descent Directions Methods

    On the Convergence to Stationary Points of Deterministic and Randomized Feasible Descent Directions Methods by Beck, Amir, Hallak, Nadav

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  6. 6
    Proximal Mapping for Symmetric Penalty and Sparsity

    Proximal Mapping for Symmetric Penalty and Sparsity by Beck, Amir, Hallak, Nadav

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  7. 7
    The regularized feasible directions method for nonconvex optimization

    The regularized feasible directions method for nonconvex optimization by Beck, Amir, Hallak, Nadav

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  8. 8
    On the Minimization Over Sparse Symmetric Sets: Projections, Optimality Conditions, and Algorithms

    On the Minimization Over Sparse Symmetric Sets: Projections, Optimality Conditions, and Algorithms by Beck, Amir, Hallak, Nadav

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  9. 9
    A non-Euclidean gradient descent method with sketching for unconstrained matrix minimization

    A non-Euclidean gradient descent method with sketching for unconstrained matrix minimization by Hallak, Nadav, Teboulle, Marc

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  10. 10
    An Augmented Lagrangian Approach to Composite Problems with a Random Linear Operator

    An Augmented Lagrangian Approach to Composite Problems with a Random Linear Operator by Greenstein, Dan, Hallak, Nadav

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  11. 11
    Regret minimization in stochastic non-convex learning via a proximal-gradient approach

    Regret minimization in stochastic non-convex learning via a proximal-gradient approach by Hallak, Nadav, Mertikopoulos, Panayotis, Cevher, Volkan

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  12. 12
    Efficient Proximal Mapping of the 1-path-norm of Shallow Networks

    Efficient Proximal Mapping of the 1-path-norm of Shallow Networks by Latorre, Fabian, Rolland, Paul, Hallak, Nadav, Cevher, Volkan

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  13. 13
    On the Almost Sure Convergence of Stochastic Gradient Descent in Non-Convex Problems

    On the Almost Sure Convergence of Stochastic Gradient Descent in Non-Convex Problems by Mertikopoulos, Panayotis, Hallak, Nadav, Kavis, Ali, Cevher, Volkan

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  14. 14
    A syndrome of severe intellectual disability, hypotonia, failure to thrive, dysmorphism, and thinning of corpus callosum maps to chromosome 7q21.13‐q21.3

    A syndrome of severe intellectual disability, hypotonia, failure to thrive, dysmorphism, and thinning of corpus callosum maps to chromosome 7q21.13‐q21.3 by Halperin, Daniel, Agam, Nadav, Hallak, Maher, Feinstein, Miora, Drabkin, Max, Yogev, Yuval, Wormser, Ohad, Shavit, Eitan, Gradstein, Libe, Shelef, Ilan, Mijalovsky, Aanalia, Flusser, Hagit, Birk, Ohad S.

    Published in Clinical genetics
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  15. 15
    Reinforcement Learning with a Terminator

    Reinforcement Learning with a Terminator by Tennenholtz, Guy, Merlis, Nadav, Shani, Lior, Mannor, Shie, Shalit, Uri, Chechik, Gal, Hallak, Assaf, Dalal, Gal

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