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09/18/2023
DeepHEN: quantitative prediction essential lncRNA genes and rethinking essentialities of lncRNA genes
Gene essentiality refers to the degree to which a gene is necessary for ...
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05/05/2023
Improved Logical Reasoning of Language Models via Differentiable Symbolic Programming
Pre-trained large language models (LMs) struggle to perform logical reas...
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04/06/2023
Do the Rewards Justify the Means? Measuring Trade-Offs Between Rewards and Ethical Behavior in the MACHIAVELLI Benchmark
Artificial agents have traditionally been trained to maximize reward, wh...
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03/27/2023
Improving the Transferability of Adversarial Examples via Direction Tuning
In the transfer-based adversarial attacks, adversarial examples are only...
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03/17/2023
Fuzziness-tuned: Improving the Transferability of Adversarial Examples
With the development of adversarial attacks, adversairal examples have b...
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12/16/2022
The Impact of Symbolic Representations on In-context Learning for Few-shot Reasoning
Pre-trained language models (LMs) have shown remarkable reasoning perfor...
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10/15/2022
A Closer Look at the Calibration of Differentially Private Learners
We systematically study the calibration of classifiers trained with diff...
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06/02/2022
FACM: Correct the Output of Deep Neural Network with Middle Layers Features against Adversarial Samples
In the strong adversarial attacks against deep neural network (DNN), the...
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06/02/2022
Mask-Guided Divergence Loss Improves the Generalization and Robustness of Deep Neural Network
Deep neural network (DNN) with dropout can be regarded as an ensemble mo...
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05/19/2022
Enhancing the Transferability of Adversarial Examples via a Few Queries
Due to the vulnerability of deep neural networks, the black-box attack h...
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02/02/2022
Can Transformers be Strong Treatment Effect Estimators?
In this paper, we develop a general framework based on the Transformer a...
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01/30/2022
Stochastic Neural Networks with Infinite Width are Deterministic
This work theoretically studies stochastic neural networks, a main type ...
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11/27/2021
Towards Principled Disentanglement for Domain Generalization
A fundamental challenge for machine learning models is generalizing to o...
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11/05/2021
Toward Learning Human-aligned Cross-domain Robust Models by Countering Misaligned Features
Machine learning has demonstrated remarkable prediction accuracy over i....
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03/29/2021
Learning Domain Invariant Representations for Generalizable Person Re-Identification
Generalizable person Re-Identification (ReID) has attracted growing atte...
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01/08/2021
Privacy-Preserving Cloud-Aided Broad Learning System
With the rapid development of artificial intelligence and the advent of ...
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01/07/2021
Blockchain Aided Privacy-Preserving Outsourcing Algorithms of Bilinear Pairings for Internet of Things Devices
Bilinear pairing is a fundamental operation that is widely used in crypt...
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01/07/2021
Machine Learning on Cloud with Blockchain: A Secure, Verifiable and Fair Approach to Outsource the Linear Regression
Linear Regression (LR) is a classical machine learning algorithm which h...
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10/23/2020