Presents the first throughput-optimal family of preemptive and non-preemptive scheduling policies for continuous multiresource job models using load-dependent discretization.
In: Pro- ceedings of the European Conference on Computer Systems (Eur oSys’15), Bordeaux, France (2015)
6 Pith papers cite this work, alongside 1,345 external citations. Polarity classification is still indexing.
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AlphaEvolve is an LLM-orchestrated evolutionary coding agent that discovered a 4x4 complex matrix multiplication algorithm using 48 scalar multiplications, the first improvement over Strassen's algorithm in 56 years, plus optimizations for Google data centers and hardware.
LoRe adaptively budgets per-step interaction evaluations in iterative graph solvers via dynamic routing, delivering 8-15x speedups and 12-44x memory reductions on MIS and TSP while preserving solution quality.
ICAN-Deploy maintains cryptographic identity invariant across canary windows for embodied agents via name-version separation, verified by proof, lint, TLA+ checking, and 100 robot trials showing zero drift.
Context Kubernetes formalizes six abstractions for knowledge orchestration in agentic AI, with experiments showing a three-tier permission model blocks all five tested attack scenarios where simpler baselines fail.
citing papers explorer
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Throughput-Optimal Multiresource-Job Scheduling with Continuous Requirement Distribution
Presents the first throughput-optimal family of preemptive and non-preemptive scheduling policies for continuous multiresource job models using load-dependent discretization.
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AlphaEvolve: A coding agent for scientific and algorithmic discovery
AlphaEvolve is an LLM-orchestrated evolutionary coding agent that discovered a 4x4 complex matrix multiplication algorithm using 48 scalar multiplications, the first improvement over Strassen's algorithm in 56 years, plus optimizations for Google data centers and hardware.
-
LoRe: Adaptive Interaction-Evaluation Routing with Per-Step Interaction Budgets for Iterative Graph Solvers
LoRe adaptively budgets per-step interaction evaluations in iterative graph solvers via dynamic routing, delivering 8-15x speedups and 12-44x memory reductions on MIS and TSP while preserving solution quality.
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ICAN-Deploy: Identity-Stable Canary Deployment for Safety-Critical Embodied Agents
ICAN-Deploy maintains cryptographic identity invariant across canary windows for embodied agents via name-version separation, verified by proof, lint, TLA+ checking, and 100 robot trials showing zero drift.
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Context Kubernetes: Declarative Orchestration of Enterprise Knowledge for Agentic AI Systems
Context Kubernetes formalizes six abstractions for knowledge orchestration in agentic AI, with experiments showing a three-tier permission model blocks all five tested attack scenarios where simpler baselines fail.
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