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09/12/2023
Answering Subjective Induction Questions on Products by Summarizing Multi-sources Multi-viewpoints Knowledge
This paper proposes a new task in the field of Answering Subjective Indu...
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06/07/2023
Robust and Efficient Fault Diagnosis of mm-Wave Active Phased Arrays using Baseband Signal
One key communication block in 5G and 6G radios is the active phased arr...
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05/30/2023
What and How does In-Context Learning Learn? Bayesian Model Averaging, Parameterization, and Generalization
In this paper, we conduct a comprehensive study of In-Context Learning (...
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04/26/2023
Scene Graph Lossless Compression with Adaptive Prediction for Objects and Relations
The scene graph is a new data structure describing objects and their pai...
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12/30/2022
An Analysis of Attention via the Lens of Exchangeability and Latent Variable Models
With the attention mechanism, transformers achieve significant empirical...
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10/20/2022
Image-Text Retrieval with Binary and Continuous Label Supervision
Most image-text retrieval work adopts binary labels indicating whether a...
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09/03/2022
Disconnected Emerging Knowledge Graph Oriented Inductive Link Prediction
Inductive link prediction (ILP) is to predict links for unseen entities ...
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06/11/2022
Federated Offline Reinforcement Learning
Evidence-based or data-driven dynamic treatment regimes are essential fo...
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12/27/2021
Wasserstein Flow Meets Replicator Dynamics: A Mean-Field Analysis of Representation Learning in Actor-Critic
Actor-critic (AC) algorithms, empowered by neural networks, have had sig...
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10/14/2021
Relation-aware Heterogeneous Graph for User Profiling
User profiling has long been an important problem that investigates user...
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09/05/2021
Shaping Individualized Impedance Landscapes for Gait Training via Reinforcement Learning
Assist-as-needed (AAN) control aims at promoting therapeutic outcomes in...
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08/19/2021
Provably Efficient Generative Adversarial Imitation Learning for Online and Offline Setting with Linear Function Approximation
In generative adversarial imitation learning (GAIL), the agent aims to l...
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08/15/2021
Deep Active Learning for Text Classification with Diverse Interpretations
Recently, Deep Neural Networks (DNNs) have made remarkable progress for ...
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02/10/2021
On the Properties of Kullback-Leibler Divergence Between Gaussians
Kullback-Leibler (KL) divergence is one of the most important divergence...
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01/28/2021
A Graph-based Relevance Matching Model for Ad-hoc Retrieval
To retrieve more relevant, appropriate and useful documents given a quer...
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12/21/2020
Variational Transport: A Convergent Particle-BasedAlgorithm for Distributional Optimization
We consider the optimization problem of minimizing a functional defined ...
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06/08/2020
Can Temporal-Difference and Q-Learning Learn Representation? A Mean-Field Theory
Temporal-difference and Q-learning play a key role in deep reinforcement...
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04/22/2020
Every Document Owns Its Structure: Inductive Text Classification via Graph Neural Networks
Text classification is fundamental in natural language processing (NLP),...
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03/08/2020
Generative Adversarial Imitation Learning with Neural Networks: Global Optimality and Convergence Rate
Generative adversarial imitation learning (GAIL) demonstrates tremendous...
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02/09/2020
Out-of-Distribution Detection with Distance Guarantee in Deep Generative Models
Recent research has shown that it is challenging to detect out-of-distri...
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11/11/2019
Learning to Order Sub-questions for Complex Question Answering
Answering complex questions involving multiple entities and relations is...
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04/11/2019
Unified Visual-Semantic Embeddings: Bridging Vision and Language with Structured Meaning Representations
We propose the Unified Visual-Semantic Embeddings (Unified VSE) for lear...
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04/11/2019