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09/06/2023
A Cole-Hopf transformation based fourth-order multiple-relaxation-time lattice Boltzmann model for the coupled Burgers' equations
In this work, a Cole-Hopf transformation based fourth-order multiple-rel...
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08/25/2023
AccFlow: Backward Accumulation for Long-Range Optical Flow
Recent deep learning-based optical flow estimators have exhibited impres...
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08/23/2023
The macroscopic finite-difference scheme and modified equations of the general propagation multiple-relaxation-time lattice Boltzmann model
In this paper, we first present the general propagation multiple-relaxat...
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07/12/2023
Towards the Better Ranking Consistency: A Multi-task Learning Framework for Early Stage Ads Ranking
Dividing ads ranking system into retrieval, early, and final stages is a...
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05/11/2023
Surgical tool classification and localization: results and methods from the MICCAI 2022 SurgToolLoc challenge
The ability to automatically detect and track surgical instruments in en...
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04/11/2023
AdaTT: Adaptive Task-to-Task Fusion Network for Multitask Learning in Recommendations
Multi-task learning (MTL) aims at enhancing the performance and efficien...
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03/31/2023
Automatic Detection of Out-of-body Frames in Surgical Videos for Privacy Protection Using Self-supervised Learning and Minimal Labels
Endoscopic video recordings are widely used in minimally invasive robot-...
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12/10/2022
Coordinate Ascent for Off-Policy RL with Global Convergence Guarantees
We revisit the domain of off-policy policy optimization in RL from the p...
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12/08/2022
Objective Surgical Skills Assessment and Tool Localization: Results from the MICCAI 2021 SimSurgSkill Challenge
Timely and effective feedback within surgical training plays a critical ...
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12/06/2022
Q-Pensieve: Boosting Sample Efficiency of Multi-Objective RL Through Memory Sharing of Q-Snapshots
Many real-world continuous control problems are in the dilemma of weighi...
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09/27/2021
Learning from Small Samples: Transformation-Invariant SVMs with Composition and Locality at Multiple Scales
Motivated by the problem of learning when the number of training samples...
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08/17/2021
A Dense Siamese U-Net trained with Edge Enhanced 3D IOU Loss for Image Co-segmentation
Image co-segmentation has attracted a lot of attentions in computer visi...
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06/08/2021
Reinforced Few-Shot Acquisition Function Learning for Bayesian Optimization
Bayesian optimization (BO) conventionally relies on handcrafted acquisit...
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02/26/2021
Surgical Visual Domain Adaptation: Results from the MICCAI 2020 SurgVisDom Challenge
Surgical data science is revolutionizing minimally invasive surgery by e...
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02/22/2021
Escaping from Zero Gradient: Revisiting Action-Constrained Reinforcement Learning via Frank-Wolfe Policy Optimization
Action-constrained reinforcement learning (RL) is a widely-used approach...
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10/08/2020
Reward-Biased Maximum Likelihood Estimation for Linear Stochastic Bandits
Modifying the reward-biased maximum likelihood method originally propose...
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01/27/2020
Developing Multi-Task Recommendations with Long-Term Rewards via Policy Distilled Reinforcement Learning
With the explosive growth of online products and content, recommendation...
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11/03/2019
Fresher Content or Smoother Playback? A Brownian-Approximation Framework for Scheduling Real-Time Wireless Video Streams
This paper presents a Brownian-approximation framework to optimize the q...
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11/03/2019
Fresher Content or Smoother Playback? A Brownian-Approximation Framework for Real-Time Video Delivery in Wireless Networks
This paper presents a Brownian-approximation framework to optimize the q...
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10/29/2019
Wasserstein F-tests and Confidence Bands for the Frèchet Regression of Density Response Curves
Data consisting of samples of probability density functions are increasi...
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07/02/2019
Bandit Learning Through Biased Maximum Likelihood Estimation
We propose BMLE, a new family of bandit algorithms, that are formulated ...
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01/14/2019
Micro- and Macro-Level Churn Analysis of Large-Scale Mobile Games
As mobile devices become more and more popular, mobile gaming has emerge...
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11/14/2018
Streaming Network Embedding through Local Actions
Recently, considerable research attention has been paid to network embed...
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10/29/2018
Heteroscedastic Bandits with Reneging
Although shown to be useful in many areas as models for solving sequenti...
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08/20/2018
A Semi-Supervised and Inductive Embedding Model for Churn Prediction of Large-Scale Mobile Games
Mobile gaming has emerged as a promising market with billion-dollar reve...
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04/13/2017
Adaptive Neighboring Selection Algorithm Based on Curvature Prediction in Manifold Learning
Recently manifold learning algorithm for dimensionality reduction attrac...
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01/13/2017
Delay-Optimal Scheduling for Queueing Systems with Switching Overhead
We study the scheduling polices for asymptotically optimal delay in queu...
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01/10/2017
Full-reference image quality assessment-based B-mode ultrasound image similarity measure
During the last decades, the number of new full-reference image quality ...
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08/26/2016
Maximum Correntropy Unscented Filter
The unscented transformation (UT) is an efficient method to solve the st...
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09/15/2015