Algeria
Stochastic Online Greedy Learning with Semi-bandit Feedbacks
In this paper, we address the online learning problem when the input to the greedy algorithm is stochastic with unknown parameters that have to be learned over time.
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Secret Collusion among AI Agents: Multi-Agent Deception via Steganography
We revisit this scenario as an experimental case study in Section 6.
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Decision Tree for Locally Private Estimation with Public Data Y uheng Ma
On one hand, the knowledge learned from public data is implicitly transferred into the private model.
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Discrete Object Generation with Reversible Inductive Construction
Ari Seff, Wenda Zhou, Farhan Damani, Abigail Doyle, Ryan P. Adams
Neural Information Processing Systems http://nips.cc/
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ERBench: An Entity-Relationship based Automatically Verifiable Hallucination Benchmark for Large Language Models
We contend that utilizing existing relational databases is a promising approach to construct a benchmark that has both merits.
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