no code implementations • 3 Dec 2023 • Peng Liu, Lemei Zhang, Terje Nissen Farup, Even W. Lauvrak, Jon Espen Ingvaldsen, Simen Eide, Jon Atle Gulla, Zhirong Yang
To bridge these gaps, we introduce NLEBench, a comprehensive benchmark tailored for evaluating natural language generation capabilities in Norwegian, a low-resource language.
no code implementations • 2 Aug 2023 • Zhirong Yang, Weijun Gao, Chong Han
Providing continuous bandwidth over several tens of GHz, the Terahertz (THz) band (0. 1-10 THz) supports space-air-ground integrated network (SAGIN) in 6G and beyond wireless networks.
1 code implementation • 12 Jun 2022 • Ruslan Khalitov, Tong Yu, Lei Cheng, Zhirong Yang
Sequential data naturally have different lengths in many domains, with some very long sequences.
Ranked #4 on Long-range modeling on LRA
1 code implementation • CVPR 2022 • Tong Yu, Ruslan Khalitov, Lei Cheng, Zhirong Yang
The overall computing cost of the new building block is as low as $O(N \log N)$.
Ranked #18 on Long-range modeling on LRA
1 code implementation • 6 Jan 2022 • Lei Cheng, Ruslan Khalitov, Tong Yu, Zhirong Yang
Recurrent Neural Networks, Transformers, and Convolutional Neural Networks are three major techniques for learning from sequential data.
no code implementations • 6 Oct 2021 • Zhirong Yang, Yuwei Chen, Jukka Corander
Second, we check the assumptions in the clustering guarantee of t-SNE and find they are often violated for real-world data sets.
1 code implementation • 16 Sep 2021 • Ruslan Khalitov, Tong Yu, Lei Cheng, Zhirong Yang
The sparse factorization method is tested for a variety of synthetic and real-world square matrices.
Ranked #17 on Long-range modeling on LRA
1 code implementation • 18 Aug 2021 • Zhirong Yang, Yuwei Chen, Denis Sedov, Samuel Kaski, Jukka Corander
In this family, much better cluster visualizations often appear with a parameter value different from the one corresponding to SNE.
no code implementations • 12 Dec 2018 • Denis Sedov, Zhirong Yang
Word embedding, which encodes words into vectors, is an important starting point in natural language processing and commonly used in many text-based machine learning tasks.
no code implementations • 16 May 2017 • Yao Lu, Zhirong Yang, Juho Kannala, Samuel Kaski
A key to the problem is learning a representation of relations.
1 code implementation • 7 Sep 2016 • Yao Lu, Jukka Corander, Zhirong Yang
To solve this problem, we introduce a fast normalization method and normalize the similarity matrix to be doubly stochastic such that all the data points have equal total similarities.
no code implementations • 5 Jun 2014 • Onur Dikmen, Zhirong Yang, Erkki Oja
Here we present a framework that facilitates automatic selection of the best divergence among a given family, based on standard maximum likelihood estimation.
no code implementations • NeurIPS 2012 • Zhirong Yang, Tele Hao, Onur Dikmen, Xi Chen, Erkki Oja
Nonnegative Matrix Factorization (NMF) is a promising relaxation technique for clustering analysis.
no code implementations • NeurIPS 2009 • Zenglin Xu, Rong Jin, Jianke Zhu, Irwin King, Michael Lyu, Zhirong Yang
In this framework, SVM and TSVM can be regarded as a learning machine without regularization and one with full regularization from the unlabeled data, respectively.
no code implementations • NeurIPS 2009 • Zhirong Yang, Irwin King, Zenglin Xu, Erkki Oja
Based on this finding, we present a parameterized subset of similarity functions for choosing the best tail-heaviness for HSSNE; (2) we present a fixed-point optimization algorithm that can be applied to all heavy-tailed functions and does not require the user to set any parameters; and (3) we present two empirical studies, one for unsupervised visualization showing that our optimization algorithm runs as fast and as good as the best known t-SNE implementation and the other for semi-supervised visualization showing quantitative superiority using the homogeneity measure as well as qualitative advantage in cluster separation over t-SNE.