Search Results for author:
Found 12 papers, 3 papers with code
A statistical method for crack detection in 3D concrete images
In practical applications, effectively segmenting cracks in large-scale computed tomography (CT) images holds significant importance for understanding the structural integrity of materials.
A Novel and Optimal Spectral Method for Permutation Synchronization
Unlike the existing methods which use $\{U_jU_1^\top\}_{j\geq 2}$, ours constructs an anchor matrix $M$ by aggregating useful information from all the block submatrices and estimates the latent permutations through $\{U_jM^\top\}_{j\geq 1}$.
Optimal and Private Learning from Human Response Data
Firstly, we obtain a refined entrywise error bound for the spectral algorithm, complementing the `average error' $\ell_2$ bound in their work.
Efficient and Accurate Learning of Mixtures of Plackett-Luce Models
We propose an initialization algorithm that can provide a provably accurate initial estimate and an EM algorithm that maximizes the true log-likelihood function efficiently.
A Spectral Approach to Item Response Theory
The Rasch model is one of the most fundamental models in \emph{item response theory} and has wide-ranging applications from education testing to recommendation systems.
Orthogonal Gated Recurrent Unit with Neumann-Cayley Transformation
In recent years, using orthogonal matrices has been shown to be a promising approach in improving Recurrent Neural Networks (RNNs) with training, stability, and convergence, particularly, to control gradients.
Efficient and Accurate Top-$K$ Recovery from Choice Data
The intersection of learning to rank and choice modeling is an active area of research with applications in e-commerce, information retrieval and the social sciences.
HYCEDIS: HYbrid Confidence Engine for Deep Document Intelligence System
Measuring the confidence of AI models is critical for safely deploying AI in real-world industrial systems.
Deep Diffusion Processes for Active Learning of Hyperspectral Images
A method for active learning of hyperspectral images (HSI) is proposed, which combines deep learning with diffusion processes on graphs.
Unsupervised Anomaly Detection on Temporal Multiway Data
These include the capacity of the compact matrix LSTM to compress noisy data near perfectly, making the strategy of compressing-decompressing data ill-suited for anomaly detection under the noise.
Improving Long Handwritten Text Line Recognition with Convolutional Multi-way Associative Memory
Convolutional Recurrent Neural Networks (CRNNs) excel at scene text recognition.
Optical Character Recognition
Optical Character Recognition (OCR)
+1
COCO: The Large Scale Black-Box Optimization Benchmarking (bbob-largescale) Test Suite
The bbob-largescale test suite, containing 24 single-objective functions in continuous domain, extends the well-known single-objective noiseless bbob test suite, which has been used since 2009 in the BBOB workshop series, to large dimension.
