no code implementations • 31 Jul 2020 • Abhishek K Dubey, Alina Peluso, Jacob Hinkle, Devanshu Agarawal, Zilong Tan
Shallow Convolution Neural Network (CNN) is a time-tested tool for the information extraction from cancer pathology reports.
2 code implementations • 27 Jun 2019 • Zilong Tan, Samuel Yeom, Matt Fredrikson, Ameet Talwalkar
In contrast, we demonstrate the promise of learning a model-aware fair representation, focusing on kernel-based models.
1 code implementation • 12 Mar 2018 • Zilong Tan, Kimberly Roche, Xiang Zhou, Sayan Mukherjee
We provide theoretical guarantees for our learning algorithms, demonstrating the robustness of parameter estimation.
1 code implementation • 21 Feb 2018 • Zilong Tan, Sayan Mukherjee
We propose a representation of Gaussian processes (GPs) based on powers of the integral operator defined by a kernel function, we call these stochastic processes integral Gaussian processes (IGPs).
no code implementations • ICML 2017 • Zilong Tan, Sayan Mukherjee
We present an efficient algorithm for learning mixed membership models when the number of variables p is much larger than the number of hidden components k. This algorithm reduces the computational complexity of state-of-the-art tensor methods, which require decomposing an $O(p^3)$ tensor, to factorizing $O(p/k)$ sub-tensors each of size $O(k^3)$.
1 code implementation • 25 Feb 2017 • Zilong Tan, Sayan Mukherjee
We present an efficient algorithm for learning mixed membership models when the number of variables $p$ is much larger than the number of hidden components $k$.