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stat.ML2021★ 5 cited
Computationally Efficient Approximations for Matrix-based Renyi's Entropy
Tieliang Gong, Yuxin Dong, Shujian Yu +1
The recently developed matrix based Renyi's entropy enables measurement of information in data simply using the eigenspectrum of symmetric positive semi definite (PSD) matrices in…
stat.ML2021
Markov subsampling based Huber Criterion
Tieliang Gong, Yuxin Dong, Hong Chen +2
Subsampling is an important technique to tackle the computational challenges brought by big data. Many subsampling procedures fall within the framework of importance sampling, whic…
stat.ML2021
Regularized Modal Regression on Markov-dependent Observations: A Theoretical Assessment
Tielang Gong, Yuxin Dong, Hong Chen +3
Modal regression, a widely used regression protocol, has been extensively investigated in statistical and machine learning communities due to its robustness to outliers and heavy-t…