A primal-dual framework with adaptive dual regularizer achieves O(√T) regret and O(√T log T) constraint violation for constrained OCO without Slater's condition under stochastic constraints, with extensions to adversarial constraints and strongly convex losses.
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2026 2verdicts
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A queueing model derives stability conditions for LLM inference services under combined compute and KV cache memory limits, with experimental validation showing typical deviations under 10%.
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Constrained Online Convex Optimization without Slater's Condition
A primal-dual framework with adaptive dual regularizer achieves O(√T) regret and O(√T log T) constraint violation for constrained OCO without Slater's condition under stochastic constraints, with extensions to adversarial constraints and strongly convex losses.
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A Queueing-Theoretic Framework for Stability Analysis of LLM Inference with KV Cache Memory Constraints
A queueing model derives stability conditions for LLM inference services under combined compute and KV cache memory limits, with experimental validation showing typical deviations under 10%.