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pro vyhledávání: '"Raff A."'
An obstetric goal for a laboring mother is to achieve a vaginal delivery as it reduces the risks inherent in major abdominal surgery (i.e., a Cesarean section). Various medical interventions may be used by a physician to increase the likelihood of th
Externí odkaz:
http://arxiv.org/abs/2408.10876
Data scientists often seek to identify the most important features in high-dimensional datasets. This can be done through $L_1$-regularized regression, but this can become inefficient for very high-dimensional datasets. Additionally, high-dimensional
Externí odkaz:
http://arxiv.org/abs/2408.10862
Previous research on testing the vulnerabilities in Large Language Models (LLMs) using adversarial attacks has primarily focused on nonsensical prompt injections, which are easily detected upon manual or automated review (e.g., via byte entropy). How
Externí odkaz:
http://arxiv.org/abs/2407.14644
As the size of datasets used in statistical learning continues to grow, distributed training of models has attracted increasing attention. These methods partition the data and exploit parallelism to reduce memory and runtime, but suffer increasingly
Externí odkaz:
http://arxiv.org/abs/2407.06346
Autor:
Mohammadi, Seyedali, Raff, Edward, Malekar, Jinendra, Palit, Vedant, Ferraro, Francis, Gaur, Manas
Language Models (LMs) are being proposed for mental health applications where the heightened risk of adverse outcomes means predictive performance may not be a sufficient litmus test of a model's utility in clinical practice. A model that can be trus
Externí odkaz:
http://arxiv.org/abs/2406.12058
While distributed training is often viewed as a solution to optimizing linear models on increasingly large datasets, inter-machine communication costs of popular distributed approaches can dominate as data dimensionality increases. Recent work on non
Externí odkaz:
http://arxiv.org/abs/2406.01753
Autor:
Liu, Chang, Saul, Rebecca, Sun, Yihao, Raff, Edward, Fuchs, Maya, Pantano, Townsend Southard, Holt, James, Micinski, Kristopher
Binary code is pervasive, and binary analysis is a key task in reverse engineering, malware classification, and vulnerability discovery. Unfortunately, while there exist large corpuses of malicious binaries, obtaining high-quality corpuses of benign
Externí odkaz:
http://arxiv.org/abs/2405.03991
Autor:
Tilwani, Deepa, Saxena, Yash, Mohammadi, Ali, Raff, Edward, Sheth, Amit, Parthasarathy, Srinivasan, Gaur, Manas
Automatic citation generation for sentences in a document or report is paramount for intelligence analysts, cybersecurity, news agencies, and education personnel. In this research, we investigate whether large language models (LLMs) are capable of ge
Externí odkaz:
http://arxiv.org/abs/2405.02228
Autor:
Sachtler, Arne, Calzolari, Davide, Raff, Maximilian, Schmidt, Annika, Wotte, Yannik P., Della Santina, Cosimo, Remy, C. David, Albu-Schäffer, Alin
Publikováno v:
2024 European Control Conference (ECC), Stockholm, Sweden, 2024, pp. 2392-2398
We identify the nonlinear normal modes spawning from the stable equilibrium of a double pendulum under gravity, and we establish their connection to homoclinic orbits through the unstable upright position as energy increases. This result is exploited
Externí odkaz:
http://arxiv.org/abs/2404.08478
Linear models are ubiquitous in data science, but are particularly prone to overfitting and data memorization in high dimensions. To guarantee the privacy of training data, differential privacy can be used. Many papers have proposed optimization tech
Externí odkaz:
http://arxiv.org/abs/2404.01141