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07/31/2023
Classification with Deep Neural Networks and Logistic Loss
Deep neural networks (DNNs) trained with the logistic loss (i.e., the cr...
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07/27/2023
TEDi: Temporally-Entangled Diffusion for Long-Term Motion Synthesis
The gradual nature of a diffusion process that synthesizes samples in sm...
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07/25/2023
Settling the Sample Complexity of Online Reinforcement Learning
A central issue lying at the heart of online reinforcement learning (RL)...
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07/16/2023
Sampling Proper Colorings on Line Graphs Using (1+o(1))Δ Colors
We prove that the single-site Glauber dynamics for sampling proper q-col...
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06/28/2023
Sharper Model-free Reinforcement Learning for Average-reward Markov Decision Processes
We develop several provably efficient model-free reinforcement learning ...
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05/16/2023
Dual-Alignment Pre-training for Cross-lingual Sentence Embedding
Recent studies have shown that dual encoder models trained with the sent...
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05/06/2023
Pre-training Language Model as a Multi-perspective Course Learner
ELECTRA, the generator-discriminator pre-training framework, has achieve...
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04/03/2023
Randomly Punctured Reed-Solomon Codes Achieve the List Decoding Capacity over Polynomial-Size Alphabets
This paper shows that, with high probability, randomly punctured Reed-So...
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03/14/2023
Two-stage Neural Network for ICASSP 2023 Speech Signal Improvement Challenge
In ICASSP 2023 speech signal improvement challenge, we developed a dual-...
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01/31/2023
Sharp Variance-Dependent Bounds in Reinforcement Learning: Best of Both Worlds in Stochastic and Deterministic Environments
We study variance-dependent regret bounds for Markov decision processes ...
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10/28/2022
RoChBert: Towards Robust BERT Fine-tuning for Chinese
Despite of the superb performance on a wide range of tasks, pre-trained ...
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10/15/2022
Near-Optimal Regret Bounds for Multi-batch Reinforcement Learning
In this paper, we study the episodic reinforcement learning (RL) probl...
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10/10/2022
Predicting Blossom Date of Cherry Tree With Support Vector Machine and Recurrent Neural Network
Our project probes the relationship between temperatures and the blossom...
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09/08/2022
Hybrid Supervised and Reinforcement Learning for the Design and Optimization of Nanophotonic Structures
From higher computational efficiency to enabling the discovery of novel ...
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07/11/2022
The HCCL System for the NIST SRE21
This paper describes the systems developed by the HCCL team for the NIST...
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05/21/2022
A Pilot Study of Relating MYCN-Gene Amplification with Neuroblastoma-Patient CT Scans
Neuroblastoma is one of the most common cancers in infants, and the init...
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05/21/2022
Mapping Emulation for Knowledge Distillation
This paper formalizes the source-blind knowledge distillation problem th...
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05/05/2022
GANimator: Neural Motion Synthesis from a Single Sequence
We present GANimator, a generative model that learns to synthesize novel...
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04/25/2022
Back-ends Selection for Deep Speaker Embeddings
Probabilistic Linear Discriminant Analysis (PLDA) was the dominant and n...
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04/21/2022
Is Neural Topic Modelling Better than Clustering? An Empirical Study on Clustering with Contextual Embeddings for Topics
Recent work incorporates pre-trained word embeddings such as BERT embedd...
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03/24/2022
Horizon-Free Reinforcement Learning in Polynomial Time: the Power of Stationary Policies
This paper gives the first polynomial-time algorithm for tabular Markov ...
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02/28/2022
Long-Tailed Classification with Gradual Balanced Loss and Adaptive Feature Generation
The real-world data distribution is essentially long-tailed, which poses...
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01/12/2022
PromptBERT: Improving BERT Sentence Embeddings with Prompts
The poor performance of the original BERT for sentence semantic similari...
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11/02/2021
iCallee: Recovering Call Graphs for Binaries
Recovering programs' call graphs is crucial for inter-procedural analysi...
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10/21/2021
Improving Non-autoregressive Generation with Mixup Training
While pre-trained language models have achieved great success on various...
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10/15/2021
Almost Optimal Batch-Regret Tradeoff for Batch Linear Contextual Bandits
We study the optimal batch-regret tradeoff for batch linear contextual b...
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05/21/2021
Learning from My Friends: Few-Shot Personalized Conversation Systems via Social Networks
Personalized conversation models (PCMs) generate responses according to ...
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03/09/2021
A New Metric on Symmetric Group and Application to Block Permutation Codes
Permutation codes have received a great attention due to various applica...
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01/29/2021
Variance-Aware Confidence Set: Variance-Dependent Bound for Linear Bandits and Horizon-Free Bound for Linear Mixture MDP
We show how to construct variance-aware confidence sets for linear bandi...
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10/12/2020
Nearly Minimax Optimal Reward-free Reinforcement Learning
We study the reward-free reinforcement learning framework, which is part...
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09/28/2020
Is Reinforcement Learning More Difficult Than Bandits? A Near-optimal Algorithm Escaping the Curse of Horizon
Episodic reinforcement learning and contextual bandits are two widely st...
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06/06/2020
Model-Free Reinforcement Learning: from Clipped Pseudo-Regret to Sample Complexity
In this paper we consider the problem of learning an ϵ-optimal policy fo...
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04/21/2020
Almost Optimal Model-Free Reinforcement Learning via Reference-Advantage Decomposition
We study the reinforcement learning problem in the setting of finite-hor...
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06/12/2019
Regret Minimization for Reinforcement Learning by Evaluating the Optimal Bias Function
We present an algorithm based on the Optimism in the Face of Uncertainty...
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03/24/2019
HAXMLNet: Hierarchical Attention Network for Extreme Multi-Label Text Classification
Extreme multi-label text classification (XMTC) addresses the problem of ...
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11/01/2018
