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08/09/2023
Intrinsic Motivation via Surprise Memory
We present a new computing model for intrinsic rewards in reinforcement ...
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01/17/2023
Memory-Augmented Theory of Mind Network
Social reasoning necessitates the capacity of theory of mind (ToM), the ...
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11/19/2022
Face Swapping as A Simple Arithmetic Operation
We propose a novel high-fidelity face swapping method called "Arithmetic...
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09/21/2022
Momentum Adversarial Distillation: Handling Large Distribution Shifts in Data-Free Knowledge Distillation
Data-free Knowledge Distillation (DFKD) has attracted attention recently...
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07/25/2022
Black-box Few-shot Knowledge Distillation
Knowledge distillation (KD) is an efficient approach to transfer the kno...
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07/08/2022
Defense Against Multi-target Trojan Attacks
Adversarial attacks on deep learning-based models pose a significant thr...
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04/20/2022
Memory-Constrained Policy Optimization
We introduce a new constrained optimization method for policy gradient r...
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04/17/2022
Learning Theory of Mind via Dynamic Traits Attribution
Machine learning of Theory of Mind (ToM) is essential to build social ag...
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02/24/2022
Towards Effective and Robust Neural Trojan Defenses via Input Filtering
Trojan attacks on deep neural networks are both dangerous and surreptiti...
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12/03/2021
Episodic Policy Gradient Training
We introduce a novel training procedure for policy gradient methods wher...
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10/26/2021
Semantic Host-free Trojan Attack
In this paper, we propose a novel host-free Trojan attack with triggers ...
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07/24/2021
Clustering by Maximizing Mutual Information Across Views
We propose a novel framework for image clustering that incorporates join...
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12/03/2020
Semi-Supervised Learning with Variational Bayesian Inference and Maximum Uncertainty Regularization
We propose two generic methods for improving semi-supervised learning (S...
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09/20/2020
Unsupervised Anomaly Detection on Temporal Multiway Data
Temporal anomaly detection looks for irregularities over space-time. Uns...
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08/26/2019
Theory and Evaluation Metrics for Learning Disentangled Representations
We make two theoretical contributions to disentanglement learning by (a)...
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12/22/2018
Graph Transformation Policy Network for Chemical Reaction Prediction
We address a fundamental problem in chemistry known as chemical reaction...
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04/01/2018
Attentional Multilabel Learning over Graphs - A message passing approach
We address a largely open problem of multilabel classification over grap...
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02/03/2018
Memory-Augmented Neural Networks for Predictive Process Analytics
Process analytics involves a sophisticated layer of data analytics built...
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01/26/2018
Knowledge Graph Embedding with Multiple Relation Projections
Knowledge graphs contain rich relational structures of the world, and th...
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08/17/2016