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Dataset Security for Machine Learning: Data Poisoning, Backdoor Attacks, and Defenses
As machine learning systems grow in scale, so do their training data req...
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Towards Defending Multiple Adversarial Perturbations via Gated Batch Normalization
There is now extensive evidence demonstrating that deep neural networks ...
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An online learning approach to dynamic pricing and capacity sizing in service systems
We study a dynamic pricing and capacity sizing problem in a GI/GI/1 queu...
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Compositional Generalization via Neural-Symbolic Stack Machines
Despite achieving tremendous success, existing deep learning models have...
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Synthesize, Execute and Debug: Learning to Repair for Neural Program Synthesis
The use of deep learning techniques has achieved significant progress fo...
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Perfect Sampling of Multivariate Hawkes Process
As an extension of self-exciting Hawkes process, the multivariate Hawkes...
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Adversarial Attacks for Embodied Agents
Adversarial attacks are valuable for providing insights into the blind-s...
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REFIT: a Unified Watermark Removal Framework for Deep Learning Systems with Limited Data
Deep neural networks (DNNs) have achieved tremendous success in various ...
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Infinite-horizon Off-Policy Policy Evaluation with Multiple Behavior Policies
We consider off-policy policy evaluation when the trajectory data are ge...
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A Neural-based Program Decompiler
Reverse engineering of binary executables is a critical problem in the c...
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Learning to Progressively Plan
For problem solving, making reactive decisions based on problem descript...
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Tree-to-tree Neural Networks for Program Translation
Program translation is an important tool to migrate legacy code in one l...
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Targeted Backdoor Attacks on Deep Learning Systems Using Data Poisoning
Deep learning models have achieved high performance on many tasks, and t...
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Can you fool AI with adversarial examples on a visual Turing test?
Deep learning has achieved impressive results in many areas of Computer ...
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Learning Neural Programs To Parse Programs
In this work, we study an important problem: learning programs from inpu...
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Latent Attention For If-Then Program Synthesis
Automatic translation from natural language descriptions into programs i...
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A General Retraining Framework for Scalable Adversarial Classification
Traditional classification algorithms assume that training and test data...
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