Zobrazeno 1 - 10
of 7 204
pro vyhledávání: '"Bastani, A."'
Autor:
Bastani, Osbert
We prove convergence guarantees for generalized low-rank matrix sensing -- i.e., where matrix sensing where the observations may be passed through some nonlinear link function. We focus on local convergence of the optimal estimator, ignoring question
Externí odkaz:
http://arxiv.org/abs/2407.10238
We consider access control for IoT systems that involves shared accesses to the IoT devices as well as their data. Since IoT devices are dispersed all over the edge of the Internet, traditional centralized access control has problems. Blockchain base
Externí odkaz:
http://arxiv.org/abs/2407.05506
Autor:
Guo, Wentao, Long, Jikai, Zeng, Yimeng, Liu, Zirui, Yang, Xinyu, Ran, Yide, Gardner, Jacob R., Bastani, Osbert, De Sa, Christopher, Yu, Xiaodong, Chen, Beidi, Xu, Zhaozhuo
Zeroth-order optimization (ZO) is a memory-efficient strategy for fine-tuning Large Language Models using only forward passes. However, the application of ZO fine-tuning in memory-constrained settings such as mobile phones and laptops is still challe
Externí odkaz:
http://arxiv.org/abs/2406.02913
Autor:
Ma, Yecheng Jason, Liang, William, Wang, Hung-Ju, Wang, Sam, Zhu, Yuke, Fan, Linxi, Bastani, Osbert, Jayaraman, Dinesh
Transferring policies learned in simulation to the real world is a promising strategy for acquiring robot skills at scale. However, sim-to-real approaches typically rely on manual design and tuning of the task reward function as well as the simulatio
Externí odkaz:
http://arxiv.org/abs/2406.01967
Conformal prediction has emerged as an effective strategy for uncertainty quantification by modifying a model to output sets of labels instead of a single label. These prediction sets come with the guarantee that they contain the true label with high
Externí odkaz:
http://arxiv.org/abs/2405.13268
We study the stochastic bandit problem with ReLU neural network structure. We show that a $\tilde{O}(\sqrt{T})$ regret guarantee is achievable by considering bandits with one-layer ReLU neural networks; to the best of our knowledge, our work is the f
Externí odkaz:
http://arxiv.org/abs/2405.07331
The growing safety concerns surrounding Large Language Models (LLMs) raise an urgent need to align them with diverse human preferences to simultaneously enhance their helpfulness and safety. A promising approach is to enforce safety constraints throu
Externí odkaz:
http://arxiv.org/abs/2405.19544
Machine learning has become an effective tool for automatically annotating unstructured data (e.g., images) with structured labels (e.g., object detections). As a result, a new programming paradigm called neurosymbolic programming has emerged where u
Externí odkaz:
http://arxiv.org/abs/2405.15912
The Internet of Things (IoT) necessitates robust access control mechanisms to secure a vast array of interconnected devices. Most of the existing IoT systems in practice use centralized solutions. We identify the problems in such solutions and adopt
Externí odkaz:
http://arxiv.org/abs/2405.15749
Large language models (LLMs) have shown impressive results at a wide-range of tasks. However, they have limitations, such as hallucinating facts and struggling with arithmetic. Recent work has addressed these issues with sophisticated decoding techni
Externí odkaz:
http://arxiv.org/abs/2405.11361