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This review presents modern gradient-free methods to solve convex optimization problems.
An automatic method for finding the greatest or least value of a function
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Randomizirovannye algoritmy otsenivaniya i optimizatsii pri pochti proizvol’nykh pomekhakh
O. Granichin and B. Polyak · 2003
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Stochastic approximation
M. T. Wasan · 2004
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Online convex optimization in the bandit setting: gradient descent without a gradient
A. D. Flaxman, A. T. Kalai, and H. B. McMahan · 2005
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Introduction to stochastic search and optimization: estimation, simulation, and control
J. C. Spall · 2005
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Prediction, learning, and games
N. Cesa-Bianchi and G. Lugosi · 2006
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The price of bandit information for online optimization
V. Dani, S. M. Kakade, and T. Hayes · 2007
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Introduction to Derivative-Free Optimization
A. R. Conn, K. Scheinberg, and L. N. Vicente · 2009
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Optimal algorithms for online convex optimization with multi-point bandit feedback
A. Agarwal, O. Dekel, and L. Xiao · 2010
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Stochastic convex optimization with bandit feedback
A. Agarwal, D. P. Foster, D. J. Hsu, S. M. Kakade, and A. Rakhlin · 2011
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Better mini-batch algorithms via accelerated gradient methods
A. Cotter, O. Shamir, N. Srebro, and K. Sridharan · 2011
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First order methods for nonsmooth convex large-scale optimization, i: general purpose methods
A. Juditsky, A. Nemirovski, et al · 2011
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Solving variational inequalities with stochastic mirror-prox algorithm
A. Juditsky, A. Nemirovski, and C. Tauvel · 2011
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Regret analysis of stochastic and nonstochastic multi-armed bandit problems
S. Bubeck, N. Cesa-Bianchi, et al · 2012
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Randomized smoothing for stochastic optimization
J. C. Duchi, P. L. Bartlett, and M. J. Wainwright · 2012
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Query complexity of derivative-free optimization
K. G. Jamieson, R. Nowak, and B. Recht · 2012
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An optimal method for stochastic composite optimization
G. Lan · 2012
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Efficiency of coordinate descent methods on huge-scale optimization problems
Y. Nesterov · 2012
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On stochastic gradient and subgradient methods with adaptive steplength sequences
F. Yousefian, A. Nedić, and U. V. Shanbhag · 2012
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Exactness, inexactness and stochasticity in first-order methods for large-scale convex optimization
O. Devolder · 2013
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On the complexity of bandit and derivative-free stochastic convex optimization
O. Shamir · 2013
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Stochastic gradient methods with inexact oracle
A. Gasnikov, P. Dvurechensky, and Y. Nesterov · 2014
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Deterministic and stochastic primal-dual subgradient algorithms for uniformly convex minimization
A. Juditsky and Y. Nesterov · 2014
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Iteration complexity of randomized block-coordinate descent methods for minimizing a composite function
P. Richtárik and M. Takáč · 2014
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Escaping the local minima via simulated annealing: Optimization of approximately convex functions
A. Belloni, T. Liang, H. Narayanan, and A. Rakhlin · 2015
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Optimal rates for zero-order convex optimization: The power of two function evaluations
J. C. Duchi, M. I. Jordan, M. J. Wainwright, and A. Wibisono · 2015
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Gradient and gradient-free methods for stochastic convex optimization with inexact oracle
A. Gasnikov, P. Dvurechensky, and D. Kamzolov · 2015
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About accelerated randomized methods
A. Gasnikov, P. Dvurechensky, and I. Usmanova · 2015
Cited alongside, same era.
Information-theoretic lower bounds for convex optimization with erroneous oracles
Y. Singer and J. Vondrák · 2015
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Coordinate descent algorithms
S. J. Wright · 2015
Cited alongside, same era.
Highly-smooth zero-th order online optimization
F. Bach and V. Perchet · 2016
Cited alongside, same era.
Learning supervised pagerank with gradient-based and gradient-free optimization methods
L. Bogolubsky, P. Dvurechenskii, A. Gasnikov, G. Gusev, Y. Nesterov, A. M. Raigorodskii, A. Tikhonov, and M. Zhukovskii · 2016
Cited alongside, same era.
Stochastic intermediate gradient method for convex problems with stochastic inexact oracle
Solving smooth min-min and min-max problems by mixed oracle algorithms
E. Gladin, A. Sadiev, A. Gasnikov, P. Dvurechensky, A. Beznosikov, and M. Alkousa · 2021
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Stochastic extragradient: General analysis and improved rates, 2021
E. Gorbunov, H. Berard, G. Gidel, and N. Loizou · 2021
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E. Gorbunov, M. Danilova, I. Shibaev, P. Dvurechensky, and A. Gasnikov · 2021
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Adaptive catalyst for smooth convex optimization
A. Ivanova, D. Pasechnyuk, D. Grishchenko, E. Shulgin, A. Gasnikov, and V. Matyukhin · 2021
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Small errors in random zeroth order optimization are imaginary
W. Jongeneel, M.-C. Yue, and D. Kuhn · 2021
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P. Dvurechensky and A. Gasnikov · 2016
Cited alongside, same era.
Gradient-free proximal methods with inexact oracle for convex stochastic nonsmooth optimization problems on the simplex
A. V. Gasnikov, A. A. Lagunovskaya, I. N. Usmanova, and F. A. Fedorenko · 2016
Cited alongside, same era.
Introduction to online convex optimization
E. Hazan et al · 2016
Cited alongside, same era.
Algorithms and matching lower bounds for approximately-convex optimization
A. Risteski and Y. Li · 2016
Cited alongside, same era.
Kernel-based methods for bandit convex optimization
S. Bubeck, Y. T. Lee, and R. Eldan · 2017
Cited alongside, same era.
Stochastic online optimization. single-point and multi-point non-linear multi-armed bandits. convex and strongly-convex case
A. V. Gasnikov, E. A. Krymova, A. A. Lagunovskaya, I. N. Usmanova, and F. A. Fedorenko · 2017
Cited alongside, same era.
Random gradient-free minimization of convex functions
Y. Nesterov and V. Spokoiny · 2017
Cited alongside, same era.
Zeroth-order algorithms for smooth saddle-point problems
A. Sadiev, A. Beznosikov, P. Dvurechensky, and A. Gasnikov · 2021
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One-point gradient-free methods for composite optimization with applications to distributed optimization, 2021
I. Stepanov, A. Voronov, A. Beznosikov, and A. Gasnikov · 2021
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Stopping rules for accelerated gradient methods with additive noise in gradient
A. Vasin, A. Gasnikov, V. Spokoiny, and P. Dvurechensky · 2021
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A gradient estimator via l1-randomization for online zero-order optimization with two point feedback
A. Akhavan, E. Chzhen, M. Pontil, and A. B. Tsybakov · 2022
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A theoretical and empirical comparison of gradient approximations in derivative-free optimization
A. S. Berahas, L. Cao, K. Choromanski, and K. Scheinberg · 2022
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Smooth monotone stochastic variational inequalities and saddle point problems–survey
A. Beznosikov, B. Polyak, E. Gorbunov, D. Kovalev, and A. Gasnikov · 2022
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Gradient-free optimization for non-smooth minimax problems with maximum value of adversarial noise
D. Dvinskikh, V. Tominin, Y. Tominin, and A. Gasnikov · 2022
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The power of first-order smooth optimization for black-box non-smooth problems
A. Gasnikov, A. Novitskii, V. Novitskii, F. Abdukhakimov, D. Kamzolov, A. Beznosikov, M. Takac, P. Dvurechensky, and B. Gu · 2022
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Vaidya’s method for convex stochastic optimization problems in small dimension
E. L. Gladin, A. V. Gasnikov, and E. Ermakova · 2022
Closest in time.
An accelerated method for derivative-free smooth stochastic convex optimization
E. Gorbunov, P. Dvurechensky, and A. Gasnikov · 2022
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Recent theoretical advances in decentralized distributed convex optimization
E. Gorbunov, A. Rogozin, A. Beznosikov, D. Dvinskikh, and A. Gasnikov · 2022
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Oracle complexity separation in convex optimization
A. Ivanova, P. Dvurechensky, E. Vorontsova, D. Pasechnyuk, A. Gasnikov, D. Dvinskikh, and A. Tyurin · 2022
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Exploiting higher-order derivatives in convex optimization methods
D. Kamzolov, A. Gasnikov, P. Dvurechensky, A. Agafonov, and M. Takáč · 2022
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C. J. Li, A. Yuan, G. Gidel, and M. I. Jordan · 2022
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Gradient-free federated learning methods with l 1 l_{1} and l 2 l_{2} -randomization for non-smooth convex stochastic optimization problems, 2022
A. Lobanov, B. Alashqar, D. Dvinskikh, and A. Gasnikov · 2022
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D. Metelev, A. Rogozin, A. Gasnikov, and D. Kovalev · 2022
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Improved exploitation of higher order smoothness in derivative-free optimization
V. Novitskii and A. Gasnikov · 2022
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Decentralized optimization over time-varying graphs: a survey
A. Rogozin, A. Gasnikov, A. Beznosikov, and D. Kovalev · 2022
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Parameter-free regret in high probability with heavy tails
J. Zhang and A. Cutkosky · 2022
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Gradient-free optimization of highly smooth functions: improved analysis and a new algorithm
A. Akhavan, E. Chzhen, M. Pontil, and A. B. Tsybakov · 2023
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Accelerated zeroth-order method for non-smooth stochastic convex optimization problem with infinite variance
N. Kornilov, O. Shamir, A. Lobanov, D. Dvinskikh, A. Gasnikov, I. A. Shibaev, E. Gorbunov, and S. Horváth · 2023
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Stochastic adversarial noise in the “black box” optimization problem
A. Lobanov · 2023
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Zero-order stochastic conditional gradient sliding method for non-smooth convex optimization
A. Lobanov, A. Anikin, A. Gasnikov, A. Gornov, and S. Chukanov · 2023
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A. Lobanov, N. Bashirov, and A. Gasnikov · 2023
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Accelerated zero-order sgd method for solving the black box optimization problem under “overparametrization” condition
A. Lobanov and A. Gasnikov · 2023
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Highly smoothness zero-order methods for solving optimization problems under pl condition
A. Lobanov, A. Gasnikov, and F. Stonyakin · 2023
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Gradient-free algorithms for solving stochastic saddle optimization problems with the polyak–łojasiewicz condition
S. Sadykov, A. Lobanov, and A. Raigorodskii · 2023
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