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Found 16 papers, 0 papers with code
PrivateLoRA For Efficient Privacy Preserving LLM
To our knowledge, our proposed framework is the first efficient and privacy-preserving LLM solution in the literature.
MultiLoRA: Democratizing LoRA for Better Multi-Task Learning
Further investigation into weight update matrices of MultiLoRA exhibits reduced dependency on top singular vectors and more democratic unitary transform contributions.
On the Opportunities of Green Computing: A Survey
To tackle the challenges of computing resources and environmental impact of AI, Green Computing has become a hot research topic.
Marketing Budget Allocation with Offline Constrained Deep Reinforcement Learning
We further show that this method is guaranteed to converge to the optimal policy, which cannot be achieved by previous value-based reinforcement learning methods for marketing budget allocation.
Adversarial Learning for Incentive Optimization in Mobile Payment Marketing
This bias deteriorates the performance of the response model and misleads the linear programming process, dramatically degrading the performance of the resulting allocation policy.
Multi-Objective Online Learning
This paper presents a systematic study of multi-objective online learning.
A Policy Efficient Reduction Approach to Convex Constrained Deep Reinforcement Learning
To apply value-based methods to CRL, a recent groundbreaking line of game-theoretic approaches uses the mixed policy that randomizes among a set of carefully generated policies to converge to the desired constraint-satisfying policy.
LinkLouvain: Link-Aware A/B Testing and Its Application on Online Marketing Campaign
In this paper, we analyze the network A/B testing problem under a real-world online marketing campaign, describe our proposed LinkLouvain method, and evaluate it on real-world data.
A Reduction Approach to Constrained Reinforcement Learning
In this paper, we present a reduction approach to find sparse policies that randomize among a constant number of policies for the constrained RL problem.
