Zobrazeno 1 - 10
of 32 918
pro vyhledávání: '"Nussbaum, A."'
Autor:
Grama, Ion, Nussbaum, Michael
Publikováno v:
Probab. Theory Relat. Fields 111, 167-214 (1998)
We establish that a non-Gaussian nonparametric regression model is asymptotically equivalent to a regression model with Gaussian noise. The approximation is in the sense of Le Cam's deficiency distance $\Delta $; the models are then asymptotically eq
Externí odkaz:
http://arxiv.org/abs/2412.15057
Autor:
Grama, Ion, Nussbaum, Michael
Publikováno v:
Ann. I.H.Poincar\'e-PR 38, 6 (2002) 923-957
We develop a Hungarian construction for the partial sum process of independent non-identically distributed random variables. The process is indexed by functions $f$ from a class $\mathcal{H}$, but the supremum over $f\in $ $\mathcal{H}$ is taken outs
Externí odkaz:
http://arxiv.org/abs/2412.15043
Autor:
Grama, Ion, Nussbaum, Michael
Publikováno v:
Mathematical Methods of Statistics, 2002, Vol. 11, No 1, pp. 1-36
We consider a nonparametric model $\mathcal{E}^{n},$ generated by independent observations $X_{i},$ $i=1,...,n,$ with densities $p(x,\theta_{i}),$ $i=1,...,n,$ the parameters of which $\theta _{i}=f(i/n)\in \Theta $ are driven by the values of an unk
Externí odkaz:
http://arxiv.org/abs/2412.14800
Autor:
Shalev-Shwartz, Shai, Shashua, Amnon, Beniamini, Gal, Levine, Yoav, Sharir, Or, Wies, Noam, Ben-Shaul, Ido, Nussbaum, Tomer, Peled, Shir Granot
Artificial Expert Intelligence (AEI) seeks to transcend the limitations of both Artificial General Intelligence (AGI) and narrow AI by integrating domain-specific expertise with critical, precise reasoning capabilities akin to those of top human expe
Externí odkaz:
http://arxiv.org/abs/2412.02441
Autor:
Suresh, Tarun, Reddy, Revanth Gangi, Xu, Yifei, Nussbaum, Zach, Mulyar, Andriy, Duderstadt, Brandon, Ji, Heng
Effective code retrieval plays a crucial role in advancing code generation, bug fixing, and software maintenance, particularly as software systems increase in complexity. While current code embedding models have demonstrated promise in retrieving cod
Externí odkaz:
http://arxiv.org/abs/2412.01007
Autor:
Kapoor, K., Hoseini, S., Choi, J., Nussbaum, B. E., Zhang, Y., Shetty, K., Skaar, C., Ward, M., Wilson, L., Shinbrough, K., Edwards, E., Wiltfong, R., Lualdi, C. P., Cohen, Offir, Kwiat, P. G., Lorenz, V. O.
We present a quantum network that distributes entangled photons between the University of Illinois Urbana-Champaign and a public library in Urbana. The network allows members of the public to perform measurements on the photons. We describe its desig
Externí odkaz:
http://arxiv.org/abs/2410.06398
This technical report describes the training of nomic-embed-vision, a highly performant, open-code, open-weights image embedding model that shares the same latent space as nomic-embed-text. Together, nomic-embed-vision and nomic-embed-text form the f
Externí odkaz:
http://arxiv.org/abs/2406.18587
Autor:
Jalota, Rricha, Verwimp, Lyan, Nussbaum-Thom, Markus, Mousa, Amr, Argueta, Arturo, Oualil, Youssef
Neural Network Language Models (NNLMs) for Virtual Assistants (VAs) are generally language-, region-, and in some cases, device-dependent, which increases the effort to scale and maintain them. Combining NNLMs for one or more of the categories is one
Externí odkaz:
http://arxiv.org/abs/2403.18783
This technical report describes the training of nomic-embed-text-v1, the first fully reproducible, open-source, open-weights, open-data, 8192 context length English text embedding model that outperforms both OpenAI Ada-002 and OpenAI text-embedding-3
Externí odkaz:
http://arxiv.org/abs/2402.01613