Search Results for author:
Found 17 papers, 4 papers with code
Streaming PAC-Bayes Gaussian process regression with a performance guarantee for online decision making
The framework offers both a guarantee of generalized performance and good accuracy.
TND-NAS: Towards Non-Differentiable Objectives in Differentiable Neural Architecture Search
Differentiable architecture search has gradually become the mainstream research topic in the field of Neural Architecture Search (NAS) for its high efficiency compared with the early NAS (EA-based, RL-based) methods.
Physics-informed generative neural network: an application to troposphere temperature prediction
The generative neural network takes the mask as prior for the second-stage refined predictions.
PAC-Bayes Bounds for Meta-learning with Data-Dependent Prior
By leveraging experience from previous tasks, meta-learning algorithms can achieve effective fast adaptation ability when encountering new tasks.
Phase Diagram of Triangular Lattice Quantum Ising Model under External Field
Quantum Ising model on a triangular lattice hosts a finite temperature Berezinskii-Kosterlitz-Thouless (BKT) phase with emergent U(1) symmetry, and it will transit into an up-up-down (UUD) phase with $C_3$ symmetry breaking upon an infinitesimal external field along the longitudinal direction, but the overall phase diagram spanned by the axes of external field and temperature remains opaque due to the lack of systematic invesitgations with controlled methodologies.
Strongly Correlated Electrons Statistical Mechanics
Channel-wise Knowledge Distillation for Dense Prediction
Observing that in semantic segmentation, some layers' feature activations of each channel tend to encode saliency of scene categories (analogue to class activation mapping), we propose to align features channel-wise between the student and teacher networks.
Global scheme of sweeping cluster algorithm to sample among topological sectors
Local constraint is closely related to the gauge field, so constrained models are usually effective low energy descriptions and important in condensed matter physics.
Statistical Mechanics Strongly Correlated Electrons
Vestigial anyon condensation in kagome quantum spin liquids
We construct a lattice model of topological order (kagome quantum spin liquids) and solve it with unbiased quantum Monte Carlo simulations.
Strongly Correlated Electrons
GenCos' Behaviors Modeling Based on Q Learning Improved by Dichotomy
Q learning is widely used to simulate the behaviors of generation companies (GenCos) in an electricity market.
Deep Variational Luenberger-type Observer for Stochastic Video Prediction
Our model builds upon an variational encoder which transforms the input video into a latent feature space and a Luenberger-type observer which captures the dynamic evolution of the latent features.
Enjoy the Untrusted Cloud: A Secure, Scalable and Efficient SQL-like Query Framework for Outsourcing Data
On one hand, such work lacks of supporting scalable access control over multiple data users.
Cryptography and Security Databases Distributed, Parallel, and Cluster Computing
DOB-Net: Actively Rejecting Unknown Excessive Time-Varying Disturbances
This paper presents an observer-integrated Reinforcement Learning (RL) approach, called Disturbance OBserver Network (DOB-Net), for robots operating in environments where disturbances are unknown and time-varying, and may frequently exceed robot control capabilities.
An Empirical Comparison of FAISS and FENSHSES for Nearest Neighbor Search in Hamming Space
In this paper, we compare the performances of FAISS and FENSHSES on nearest neighbor search in Hamming space--a fundamental task with ubiquitous applications in nowadays eCommerce.
Fast and Exact Nearest Neighbor Search in Hamming Space on Full-Text Search Engines
A growing interest has been witnessed recently from both academia and industry in building nearest neighbor search (NNS) solutions on top of full-text search engines.
Deep Uncertainty Quantification: A Machine Learning Approach for Weather Forecasting
We cast the weather forecasting problem as an end-to-end deep learning problem and solve it by proposing a novel negative log-likelihood error (NLE) loss function.
Towards Practical Visual Search Engine within Elasticsearch
In this paper, we describe our end-to-end content-based image retrieval system built upon Elasticsearch, a well-known and popular textual search engine.
Revisiting Skip-Gram Negative Sampling Model with Rectification
We revisit skip-gram negative sampling (SGNS), one of the most popular neural-network based approaches to learning distributed word representation.
