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09/10/2023
Bicoptor 2.0: Addressing Challenges in Probabilistic Truncation for Enhanced Privacy-Preserving Machine Learning
This paper primarily focuses on analyzing the problems and proposing sol...
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06/09/2023
Throughput of Hybrid UAV Networks with Scale-Free Topology
Unmanned Aerial Vehicles (UAVs) hold great potential to support a wide r...
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05/28/2023
Distill Gold from Massive Ores: Efficient Dataset Distillation via Critical Samples Selection
Data-efficient learning has drawn significant attention, especially give...
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05/26/2023
HUB: Guiding Learned Optimizers with Continuous Prompt Tuning
Learned optimizers are a crucial component of meta-learning. Recent adva...
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05/23/2023
Bulk-Switching Memristor-based Compute-In-Memory Module for Deep Neural Network Training
The need for deep neural network (DNN) models with higher performance an...
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04/13/2023
PowerGAN: A Machine Learning Approach for Power Side-Channel Attack on Compute-in-Memory Accelerators
Analog compute-in-memory (CIM) accelerators are becoming increasingly po...
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04/10/2023
Neural Residual Radiance Fields for Streamably Free-Viewpoint Videos
The success of the Neural Radiance Fields (NeRFs) for modeling and free-...
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03/19/2023
RN-Net: Reservoir Nodes-Enabled Neuromorphic Vision Sensing Network
Event-based cameras are inspired by the sparse and asynchronous spike re...
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03/09/2023
NoiseCAM: Explainable AI for the Boundary Between Noise and Adversarial Attacks
Deep Learning (DL) and Deep Neural Networks (DNNs) are widely used in va...
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02/16/2023
Object-centric Learning with Cyclic Walks between Parts and Whole
Learning object-centric representations from complex natural environment...
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12/10/2022
HumanGen: Generating Human Radiance Fields with Explicit Priors
Recent years have witnessed the tremendous progress of 3D GANs for gener...
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11/10/2022
Zebra: Deeply Integrating System-Level Provenance Search and Tracking for Efficient Attack Investigation
System auditing has emerged as a key approach for monitoring system call...
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10/29/2022
Spectral Representation Learning for Conditional Moment Models
Many problems in causal inference and economics can be formulated in the...
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10/05/2022
Bicoptor: Two-round Secure Three-party Non-linear Computation without Preprocessing for Privacy-preserving Machine Learning
The overhead of non-linear functions dominates the performance of the se...
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09/30/2022
Application of Deep Q Learning with Stimulation Results for Elevator Optimization
This paper presents a methodology for combining programming and mathemat...
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09/21/2022
Modeling Perceptual Loudness of Piano Tone: Theory and Applications
The relationship between perceptual loudness and physical attributes of ...
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09/06/2022
Side-channel attack analysis on in-memory computing architectures
In-memory computing (IMC) systems have great potential for accelerating ...
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08/22/2022
SWEM: Towards Real-Time Video Object Segmentation with Sequential Weighted Expectation-Maximization
Matching-based methods, especially those based on space-time memory, are...
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05/22/2022
Fast Instrument Learning with Faster Rates
We investigate nonlinear instrumental variable (IV) regression given hig...
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03/08/2022
NeReF: Neural Refractive Field for Fluid Surface Reconstruction and Implicit Representation
Existing neural reconstruction schemes such as Neural Radiance Field (Ne...
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01/28/2022
DynaMixer: A Vision MLP Architecture with Dynamic Mixing
Recently, MLP-like vision models have achieved promising performances on...
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12/30/2021
Audio-to-symbolic Arrangement via Cross-modal Music Representation Learning
Could we automatically derive the score of a piano accompaniment based o...
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10/26/2021
C^2SP-Net: Joint Compression and Classification Network for Epilepsy Seizure Prediction
Recent development in brain-machine interface technology has made seizur...
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08/12/2021
iButter: Neural Interactive Bullet Time Generator for Human Free-viewpoint Rendering
Generating “bullet-time” effects of human free-viewpoint videos is criti...
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06/16/2021
Scalable Quasi-Bayesian Inference for Instrumental Variable Regression
Recent years have witnessed an upsurge of interest in employing flexible...
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05/05/2021
A Novel Multi-scale Dilated 3D CNN for Epileptic Seizure Prediction
Accurate prediction of epileptic seizures allows patients to take preven...
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04/28/2021
Autoregressive Dynamics Models for Offline Policy Evaluation and Optimization
Standard dynamics models for continuous control make use of feedforward ...
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04/06/2021
MirrorNeRF: One-shot Neural Portrait RadianceField from Multi-mirror Catadioptric Imaging
Photo-realistic neural reconstruction and rendering of the human portrai...
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03/30/2021
Benchmarks for Deep Off-Policy Evaluation
Off-policy evaluation (OPE) holds the promise of being able to leverage ...
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03/17/2021
Regularized Behavior Value Estimation
Offline reinforcement learning restricts the learning process to rely on...
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12/14/2020
Fork or Fail: Cycle-Consistent Training with Many-to-One Mappings
Cycle-consistent training is widely used for jointly learning a forward ...
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11/27/2020
Offline Learning from Demonstrations and Unlabeled Experience
Behavior cloning (BC) is often practical for robot learning because it a...
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10/25/2020
Further Analysis of Outlier Detection with Deep Generative Models
The recent, counter-intuitive discovery that deep generative models (DGM...
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08/17/2020
POP909: A Pop-song Dataset for Music Arrangement Generation
Music arrangement generation is a subtask of automatic music generation,...
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08/17/2020
Learning Interpretable Representation for Controllable Polyphonic Music Generation
While deep generative models have become the leading methods for algorit...
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08/17/2020
PIANOTREE VAE: Structured Representation Learning for Polyphonic Music
The dominant approach for music representation learning involves the dee...
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07/17/2020
Hyperparameter Selection for Offline Reinforcement Learning
Offline reinforcement learning (RL purely from logged data) is an import...
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06/26/2020
Critic Regularized Regression
Offline reinforcement learning (RL), also known as batch RL, offers the ...
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06/24/2020
RL Unplugged: Benchmarks for Offline Reinforcement Learning
Offline methods for reinforcement learning have the potential to help br...
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06/01/2020
Acme: A Research Framework for Distributed Reinforcement Learning
Deep reinforcement learning has led to many recent-and groundbreaking-ad...
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02/18/2020
A Wasserstein Minimum Velocity Approach to Learning Unnormalized Models
Score matching provides an effective approach to learning flexible unnor...
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01/14/2020
Incentive Analysis of Bitcoin-NG, Revisited
Bitcoin-NG is among the first blockchain protocols to approach the near-...
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12/23/2019
The Usual Suspects? Reassessing Blame for VAE Posterior Collapse
In narrow asymptotic settings Gaussian VAE models of continuous data hav...
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10/02/2019
Task-Relevant Adversarial Imitation Learning
We show that a critical problem in adversarial imitation from high-dimen...
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09/26/2019
A Framework for Data-Driven Robotics
We present a framework for data-driven robotics that makes use of a larg...
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09/03/2019
Making Efficient Use of Demonstrations to Solve Hard Exploration Problems
This paper introduces R2D3, an agent that makes efficient use of demonst...
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07/18/2019
Towards a Multi-Chain Future of Proof-of-Space
Proof-of-Space provides an intriguing alternative for consensus protocol...
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06/09/2019
Deep Music Analogy Via Latent Representation Disentanglement
Analogy is a key solution to automated music generation, featured by its...
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02/26/2019
Function Space Particle Optimization for Bayesian Neural Networks
While Bayesian neural networks (BNNs) have drawn increasing attention, t...
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12/28/2018