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07/02/2023
Defending Against Malicious Behaviors in Federated Learning with Blockchain
In the era of deep learning, federated learning (FL) presents a promisin...
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06/22/2023
Squeeze, Recover and Relabel: Dataset Condensation at ImageNet Scale From A New Perspective
We present a new dataset condensation framework termed Squeeze, Recover ...
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06/13/2023
One-for-All: Generalized LoRA for Parameter-Efficient Fine-tuning
We present Generalized LoRA (GLoRA), an advanced approach for universal ...
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05/23/2023
3D Open-vocabulary Segmentation with Foundation Models
Open-vocabulary segmentation of 3D scenes is a fundamental function of h...
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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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04/03/2023
3D Semantic Segmentation in the Wild: Learning Generalized Models for Adverse-Condition Point Clouds
Robust point cloud parsing under all-weather conditions is crucial to le...
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03/30/2023
KD-DLGAN: Data Limited Image Generation via Knowledge Distillation
Generative Adversarial Networks (GANs) rely heavily on large-scale train...
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03/19/2023
StyleRF: Zero-shot 3D Style Transfer of Neural Radiance Fields
3D style transfer aims to render stylized novel views of a 3D scene with...
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03/08/2023
Memory-adaptive Depth-wise Heterogenous Federated Learning
Federated learning is a promising paradigm that allows multiple clients ...
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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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10/20/2022
MixMask: Revisiting Masked Siamese Self-supervised Learning in Asymmetric Distance
Recent advances in self-supervised learning integrate Masked Modeling an...
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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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01/03/2022
Vision Transformer Slimming: Multi-Dimension Searching in Continuous Optimization Space
This paper explores the feasibility of finding an optimal sub-model from...
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12/03/2021
Data-Free Neural Architecture Search via Recursive Label Calibration
This paper aims to explore the feasibility of neural architecture search...
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12/02/2021
A Fast Knowledge Distillation Framework for Visual Recognition
While Knowledge Distillation (KD) has been recognized as a useful tool i...
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11/29/2021
Nonuniform-to-Uniform Quantization: Towards Accurate Quantization via Generalized Straight-Through Estimation
The nonuniform quantization strategy for compressing neural networks usu...
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11/11/2021
Learning from Mistakes – A Framework for Neural Architecture Search
Learning from one's mistakes is an effective human learning technique wh...
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11/09/2021
Sliced Recursive Transformer
We present a neat yet effective recursive operation on vision transforme...
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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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11/05/2021
Tradeoffs of Linear Mixed Models in Genome-wide Association Studies
Motivated by empirical arguments that are well-known from the genome-wid...
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11/03/2021
Multi-task Learning of Order-Consistent Causal Graphs
We consider the problem of discovering K related Gaussian directed acycl...
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06/17/2021
Prototypical Graph Contrastive Learning
Graph-level representations are critical in various real-world applicati...
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05/20/2021
Negational Symmetry of Quantum Neural Networks for Binary Pattern Classification
Entanglement is a physical phenomenon, which has fueled recent successes...
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02/24/2021
Active Learning to Classify Macromolecular Structures in situ for Less Supervision in Cryo-Electron Tomography
Motivation: Cryo-Electron Tomography (cryo-ET) is a 3D bioimaging tool t...
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01/30/2021
On Data Efficiency of Meta-learning
Meta-learning has enabled learning statistical models that can be quickl...
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10/11/2020
Federated Learning via Posterior Averaging: A New Perspective and Practical Algorithms
Federated learning is typically approached as an optimization problem, w...
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06/17/2020
XRayGAN: Consistency-preserving Generation of X-ray Images from Radiology Reports
To effectively train medical students to become qualified radiologists, ...
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05/11/2020
On the Generation of Medical Dialogues for COVID-19
Under the pandemic of COVID-19, people experiencing COVID19-related symp...
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04/26/2020
Show, Describe and Conclude: On Exploiting the Structure Information of Chest X-Ray Reports
Chest X-Ray (CXR) images are commonly used for clinical screening and di...
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04/07/2020
Learning from Imperfect Annotations
Many machine learning systems today are trained on large amounts of huma...
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03/07/2020
PathVQA: 30000+ Questions for Medical Visual Question Answering
Is it possible to develop an "AI Pathologist" to pass the board-certifie...
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09/28/2019
Generalized Zero-shot ICD Coding
The International Classification of Diseases (ICD) is a list of classifi...
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06/12/2019
Efficient Exploration via State Marginal Matching
To solve tasks with sparse rewards, reinforcement learning algorithms mu...
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05/31/2019
Regularizing Black-box Models for Improved Interpretability (HILL 2019 Version)
Most of the work on interpretable machine learning has focused on design...
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03/29/2019
SysML: The New Frontier of Machine Learning Systems
Machine learning (ML) techniques are enjoying rapidly increasing adoptio...
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02/19/2019
Explaining a black-box using Deep Variational Information Bottleneck Approach
Briefness and comprehensiveness are necessary in order to give a lot of ...
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02/18/2019
Regularizing Black-box Models for Improved Interpretability
Most work on interpretability in machine learning has focused on designi...
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01/31/2019
ProBO: a Framework for Using Probabilistic Programming in Bayesian Optimization
Optimizing an expensive-to-query function is a common task in science an...
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01/28/2019
Toward Unsupervised Text Content Manipulation
Controlled generation of text is of high practical use. Recent efforts h...
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01/01/2019
Text Infilling
Recent years have seen remarkable progress of text generation in differe...
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11/24/2018
Connecting the Dots Between MLE and RL for Sequence Generation
Sequence generation models such as recurrent networks can be trained wit...
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11/20/2018
Unsupervised Pseudo-Labeling for Extractive Summarization on Electronic Health Records
Extractive summarization is very useful for physicians to better manage ...
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11/16/2018
On the Complexity of Exploration in Goal-Driven Navigation
Building agents that can explore their environments intelligently is a c...
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10/31/2018
Multimodal Machine Learning for Automated ICD Coding
This study presents a multimodal machine learning model to predict ICD-1...
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10/04/2018
AutoLoss: Learning Discrete Schedules for Alternate Optimization
Many machine learning problems involve iteratively and alternately optim...
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08/05/2018
Missing Value Imputation Based on Deep Generative Models
Missing values widely exist in many real-world datasets, which hinders t...
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07/10/2018
CIRL: Controllable Imitative Reinforcement Learning for Vision-based Self-driving
Autonomous urban driving navigation with complex multi-agent dynamics is...
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07/10/2018
Geometric Generalization Based Zero-Shot Learning Dataset Infinite World: Simple Yet Powerful
Raven's Progressive Matrices are one of the widely used tests in evaluat...
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06/26/2018
Deep Generative Models with Learnable Knowledge Constraints
The broad set of deep generative models (DGMs) has achieved remarkable a...
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06/17/2018