Xiaohan Chen

According to our database1, Xiaohan Chen authored at least 26 papers between 2006 and 2020.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Other 

Links

On csauthors.net:

Bibliography

2020
ShiftAddNet: A Hardware-Inspired Deep Network.
CoRR, 2020

Safeguarded Learned Convex Optimization.
CoRR, 2020

SmartExchange: Trading Higher-cost Memory Storage/Access for Lower-cost Computation.
Proceedings of the 47th ACM/IEEE Annual International Symposium on Computer Architecture, 2020

Drawing Early-Bird Tickets: Toward More Efficient Training of Deep Networks.
Proceedings of the 8th International Conference on Learning Representations, 2020

Uncertainty Quantification for Deep Context-Aware Mobile Activity Recognition and Unknown Context Discovery.
Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

2019
E2-Train: Energy-Efficient Deep Network Training with Data-, Model-, and Algorithm-Level Saving.
CoRR, 2019

Drawing early-bird tickets: Towards more efficient training of deep networks.
CoRR, 2019

E2-Train: Training State-of-the-art CNNs with Over 80% Energy Savings.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Plug-and-Play Methods Provably Converge with Properly Trained Denoisers.
Proceedings of the 36th International Conference on Machine Learning, 2019

ALISTA: Analytic Weights Are As Good As Learned Weights in LISTA.
Proceedings of the 7th International Conference on Learning Representations, 2019

2018
Can We Gain More from Orthogonality Regularizations in Training Deep CNNs?
CoRR, 2018

Theoretical Linear Convergence of Unfolded ISTA and Its Practical Weights and Thresholds.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Can We Gain More from Orthogonality Regularizations in Training Deep Networks?
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Unsupervised Speech Denoising Method Based on Deep Neural Network.
Proceedings of the 11th International Symposium on Computational Intelligence and Design, 2018

2015
Pose estimation of robotic end-effectors under low speed motion using EKF with inertial and SE(3) measurements.
Proceedings of the IEEE International Conference on Advanced Intelligent Mechatronics, 2015

2014
Tracking Control for Differential-Drive Mobile Robots With Diamond-Shaped Input Constraints.
IEEE Trans. Control. Syst. Technol., 2014

Tracking control of nonholonomic mobile robots with velocity and acceleration constraints.
Proceedings of the American Control Conference, 2014

2011
Column formation control of multi-robot systems with input constraints.
Proceedings of the 50th IEEE Conference on Decision and Control and European Control Conference, 2011

2010
Automatic target recognition performance losses in the presence of atmospheric and camera effects.
J. Electronic Imaging, 2010

A behavior-based SMS antispam system.
IBM J. Res. Dev., 2010

2009
Empirical Capacity of a Recognition Channel for Single- and Multipose Object Recognition Under the Constraint of PCA Encoding.
IEEE Trans. Image Process., 2009

2008
On empirical capacity, random coding bound, and probability of outage of an object recognition system under constraint of PCA-encoding.
Proceedings of the 42nd Annual Conference on Information Sciences and Systems, 2008

2007
On Generation and Analysis of Synthetic Iris Images.
IEEE Trans. Inf. Forensics Secur., 2007

On Capacity of Automatic Target Recognition Systems Under the Constraint of PCA-Encoding.
Proceedings of the 41st Annual Conference on Information Sciences and Systems, 2007

2006
On Performance Comparison of Real and Synthetic Iris Images.
Proceedings of the International Conference on Image Processing, 2006

A Joint Shape-Intensity Estimation in Computerized Tomography in the Presence of High-Density Objects.
Proceedings of the International Conference on Image Processing, 2006


  Loading...