Pages that link to "Item:Q5272322"
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The following pages link to Information-Based Complexity, Feedback and Dynamics in Convex Programming (Q5272322):
Displaying 14 items.
- The exact information-based complexity of smooth convex minimization (Q511109) (← links)
- Localization of VC classes: beyond local Rademacher complexities (Q1663641) (← links)
- Stochastic gradient descent with Polyak's learning rate (Q1983178) (← links)
- Surrogate losses in passive and active learning (Q2008623) (← links)
- Oracle lower bounds for stochastic gradient sampling algorithms (Q2137007) (← links)
- Sub-linear convergence of a stochastic proximal iteration method in Hilbert space (Q2162529) (← links)
- Lower error bounds for the stochastic gradient descent optimization algorithm: sharp convergence rates for slowly and fast decaying learning rates (Q2303416) (← links)
- Deterministic and stochastic primal-dual subgradient algorithms for uniformly convex minimization (Q2921184) (← links)
- Information Relaxations, Duality, and Convex Stochastic Dynamic Programs (Q2941432) (← links)
- Statistical Query Algorithms for Mean Vector Estimation and Stochastic Convex Optimization (Q4575825) (← links)
- Optimization Methods for Large-Scale Machine Learning (Q4641709) (← links)
- Accelerated Stochastic Algorithms for Convex-Concave Saddle-Point Problems (Q5085148) (← links)
- Computing the value of information of quadratic decision problems and its non-negativity conditions (Q5356927) (← links)
- Lower bounds for non-convex stochastic optimization (Q6038643) (← links)
