Zobrazeno 1 - 10
of 8 881
pro vyhledávání: '"Vuong, P."'
We consider the problem of sampling a multimodal distribution with a Markov chain given a small number of samples from the stationary measure. Although mixing can be arbitrarily slow, we show that if the Markov chain has a $k$th order spectral gap, i
Externí odkaz:
http://arxiv.org/abs/2411.09117
Autor:
Lee, David H., Prasad, Aditya, Vuong, Ramiro Deo-Campo, Wang, Tianyu, Han, Eric, Kempe, David
Dynamic programming (DP) is a fundamental and powerful algorithmic paradigm taught in most undergraduate (and many graduate) algorithms classes. DP problems are challenging for many computer science students because they require identifying unique pr
Externí odkaz:
http://arxiv.org/abs/2411.07705
Commonsense datasets have been well developed in Natural Language Processing, mainly through crowdsource human annotation. However, there are debates on the genuineness of commonsense reasoning benchmarks. In specific, a significant portion of instan
Externí odkaz:
http://arxiv.org/abs/2411.03964
Autor:
Black, Kevin, Brown, Noah, Driess, Danny, Esmail, Adnan, Equi, Michael, Finn, Chelsea, Fusai, Niccolo, Groom, Lachy, Hausman, Karol, Ichter, Brian, Jakubczak, Szymon, Jones, Tim, Ke, Liyiming, Levine, Sergey, Li-Bell, Adrian, Mothukuri, Mohith, Nair, Suraj, Pertsch, Karl, Shi, Lucy Xiaoyang, Tanner, James, Vuong, Quan, Walling, Anna, Wang, Haohuan, Zhilinsky, Ury
Robot learning holds tremendous promise to unlock the full potential of flexible, general, and dexterous robot systems, as well as to address some of the deepest questions in artificial intelligence. However, bringing robot learning to the level of g
Externí odkaz:
http://arxiv.org/abs/2410.24164
Adversarial machine learning concerns situations in which learners face attacks from active adversaries. Such scenarios arise in applications such as spam email filtering, malware detection and fake-image generation, where security methods must be ac
Externí odkaz:
http://arxiv.org/abs/2410.20284
Autor:
Binz, Marcel, Akata, Elif, Bethge, Matthias, Brändle, Franziska, Callaway, Fred, Coda-Forno, Julian, Dayan, Peter, Demircan, Can, Eckstein, Maria K., Éltető, Noémi, Griffiths, Thomas L., Haridi, Susanne, Jagadish, Akshay K., Ji-An, Li, Kipnis, Alexander, Kumar, Sreejan, Ludwig, Tobias, Mathony, Marvin, Mattar, Marcelo, Modirshanechi, Alireza, Nath, Surabhi S., Peterson, Joshua C., Rmus, Milena, Russek, Evan M., Saanum, Tankred, Scharfenberg, Natalia, Schubert, Johannes A., Buschoff, Luca M. Schulze, Singhi, Nishad, Sui, Xin, Thalmann, Mirko, Theis, Fabian, Truong, Vuong, Udandarao, Vishaal, Voudouris, Konstantinos, Wilson, Robert, Witte, Kristin, Wu, Shuchen, Wulff, Dirk, Xiong, Huadong, Schulz, Eric
Establishing a unified theory of cognition has been a major goal of psychology. While there have been previous attempts to instantiate such theories by building computational models, we currently do not have one model that captures the human mind in
Externí odkaz:
http://arxiv.org/abs/2410.20268
Autor:
Bui, Vuong, Rosenfeld, Matthieu
We study some properties of the growth rate of $\mathcal{L}(\mathcal{A},\mathcal{F})$, that is, the language of words over the alphabet $\mathcal{A}$ avoiding the set of forbidden factors $\mathcal{F}$. We first provide a sufficient condition on $\ma
Externí odkaz:
http://arxiv.org/abs/2410.19654
Autor:
Bui, Vuong
Generalizing some popular sequences like Catalan's number, Schr\"oder's number, etc, we consider the sequence $s_n$ with $s_0=1$ and for $n\ge 1$, \begin{multline*} s_n=\sum_{x_1+\dots+x_{\ell_1}=n-1} \kappa_1 s_{x_1}\dots s_{x_{\ell_1}} + \dots +\su
Externí odkaz:
http://arxiv.org/abs/2410.18534
Diffusion models excel at generating visually striking content from text but can inadvertently produce undesirable or harmful content when trained on unfiltered internet data. A practical solution is to selectively removing target concepts from the m
Externí odkaz:
http://arxiv.org/abs/2410.15618
Autor:
Nguyen, Hai-Long, Nguyen, Tan-Minh, Nguyen, Duc-Minh, Vuong, Thi-Hai-Yen, Nguyen, Ha-Thanh, Phan, Xuan-Hieu
Statutory law retrieval is a typical problem in legal language processing, that has various practical applications in law engineering. Modern deep learning-based retrieval methods have achieved significant results for this problem. However, retrieval
Externí odkaz:
http://arxiv.org/abs/2410.12154