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05/29/2023
Make-An-Audio 2: Temporal-Enhanced Text-to-Audio Generation
Large diffusion models have been successful in text-to-audio (T2A) synth...
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05/18/2023
On the Statistical Efficiency of Mean Field Reinforcement Learning with General Function Approximation
In this paper, we study the statistical efficiency of Reinforcement Lear...
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05/01/2023
GeneFace++: Generalized and Stable Real-Time Audio-Driven 3D Talking Face Generation
Generating talking person portraits with arbitrary speech audio is a cru...
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04/25/2023
AudioGPT: Understanding and Generating Speech, Music, Sound, and Talking Head
Large language models (LLMs) have exhibited remarkable capabilities acro...
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03/11/2023
Online Neural Path Guiding with Normalized Anisotropic Spherical Gaussians
The variance reduction speed of physically-based rendering is heavily af...
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03/08/2023
Structure-aware registration network for liver DCE-CT images
Image registration of liver dynamic contrast-enhanced computed tomograph...
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02/10/2023
Robust Knowledge Transfer in Tiered Reinforcement Learning
In this paper, we study the Tiered Reinforcement Learning setting, a par...
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01/30/2023
Make-An-Audio: Text-To-Audio Generation with Prompt-Enhanced Diffusion Models
Large-scale multimodal generative modeling has created milestones in tex...
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10/09/2022
Coresets for Wasserstein Distributionally Robust Optimization Problems
Wasserstein distributionally robust optimization () is a popular model t...
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06/14/2022
Learning towards Synchronous Network Memorizability and Generalizability for Continual Segmentation across Multiple Sites
In clinical practice, a segmentation network is often required to contin...
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05/25/2022
Tiered Reinforcement Learning: Pessimism in the Face of Uncertainty and Constant Regret
We propose a new learning framework that captures the tiered structure o...
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04/03/2022
Kernel Extreme Learning Machine Optimized by the Sparrow Search Algorithm for Hyperspectral Image Classification
To improve the classification performance and generalization ability of ...
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02/14/2022
Towards Deployment-Efficient Reinforcement Learning: Lower Bound and Optimality
Deployment efficiency is an important criterion for many real-world appl...
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12/05/2021
A Novel Sequential Coreset Method for Gradient Descent Algorithms
A wide range of optimization problems arising in machine learning can be...
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06/02/2021
On the Convergence Rate of Off-Policy Policy Optimization Methods with Density-Ratio Correction
In this paper, we study the convergence properties of off-policy policy ...
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02/28/2021
Is Simple Uniform Sampling Efficient for Center-Based Clustering With Outliers: When and Why?
Clustering has many important applications in computer science, but real...
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07/23/2020
WeightNet: Revisiting the Design Space of Weight Networks
We present a conceptually simple, flexible and effective framework for w...
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06/14/2020
Defending SVMs against Poisoning Attacks: the Hardness and DBSCAN Approach
Adversarial machine learning has attracted a great amount of attention i...
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02/27/2020
The Effectiveness of Johnson-Lindenstrauss Transform for High Dimensional Optimization with Outliers
Johnson-Lindenstrauss (JL) Transform is one of the most popular methods ...
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02/06/2020
Minimax Confidence Interval for Off-Policy Evaluation and Policy Optimization
We study minimax methods for off-policy evaluation (OPE) using value-fun...
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10/20/2019
From Importance Sampling to Doubly Robust Policy Gradient
We show that policy gradient (PG) and its variance reduction variants ca...
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03/17/2018
Learning to Cluster for Proposal-Free Instance Segmentation
This work proposed a novel learning objective to train a deep neural net...
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09/02/2017
Learning Loss for Knowledge Distillation with Conditional Adversarial Networks
There is an increasing interest on accelerating neural networks for real...
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06/28/2017
Robust Lane Tracking with Multi-mode Observation Model and Particle Filtering
Automatic lane tracking involves estimating the underlying signal from a...
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05/02/2017