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• [J44] Nested replicator dynamics, nested logit choice, and similarity-based learning
• [J43] The rate of convergence of Bregman proximal methods: Local geometry vs. regularity vs. sharpness
• [J42] Quick or cheap? Breaking points in dynamic markets
• [J41] A unified stochastic approximation framework for learning in games
• [J40] Multi-agent online learning in time-varying games
• [J39] Survival of dominated strategies under imitation dynamics
• [J38] Learning in nonatomic games, Part I: Finite action spaces and population games
• [J37] Distributed stochastic optimization with large delays
• [J36] Multi-agent online optimization with delays: Asynchronicity, adaptivity, and optimism
• [J35] Online reconfiguration of IoT applications in the Fog: The information-coordination trade-off
• [J34] Minibatch forward-backward-forward methods for solving stochastic variational inequalities
• [J33] Robust power management via learning and game design
• [J32] Fast optimization with zeroth-order feedback in distributed multi-user MIMO systems
• [J31] On the convergence of mirror descent beyond stochastic convex programming
• [J30] When is selfish routing bad? The price of anarchy in light and heavy traffic
• [J29] Hessian barrier algorithms for linearly constrained optimization problems
• [J28] Online power optimization in feedback-limited, dynamic and unpredictable IoT networks
• [J27] Learning in games with continuous action sets and unknown payoff functions
• [J26] Stochastic mirror descent dynamics and their convergence in monotone variational inequalities
• [J25] Riemannian game dynamics
• [J24] On the convergence of gradient-like flows with noisy gradient input
• [J23] On the robustness of learning in games with stochastically perturbed payoff observations
• [J22] Distributed stochastic optimization via matrix exponential learning
• [J21] A continuous-time approach to online optimization
• [J20] Semi-cognitive radio networks: A novel dynamic spectrum sharing mechanism
• [J19] Auction-based resource allocation in OpenFlow multi-tenant networks
• [J18] Mixed-strategy learning with continuous action sets
• [J17] Learning in games via reinforcement and regularization
• [J16] Power optimization in random wireless networks
• [J15] A stochastic approximation algorithm for stochastic semidefinite programming
• [J14] Learning to be green: Robust energy efficiency maximization in dynamic MIMO-OFDM systems
• [J13] Imitation dynamics with payoff shocks
• [J12] Learning in an uncertain world: MIMO covariance matrix optimization with imperfect feedback
• [J11] Inertial game dynamics and applications to constrained optimization
• [J10] Interference-based pricing for opportunistic multi-carrier cognitive radio systems
• [J9] Energy-aware competitive power allocation for heterogeneous networks under QoS constraints
• [J8] Penalty-regulated dynamics and robust learning procedures in games
• [J7] Transmit without regrets: Online optimization in MIMO–OFDM cognitive radio systems
• [J6] Higher-order game dynamics
• [J5] Distributed learning policies for power allocation in multiple access channels
• [J4] Neutral stability, drift, and the diversification of languages
• [J3] Living at the edge: A large deviations approach to the outage MIMO capacity
• [J2] The emergence of rational behavior in the presence of stochastic perturbations
• [J1] Correlated anarchy in overlapping wireless networks