… Initially, we evaluate how well our model can learn to predict permutation matrices from
shuffled … As performance metrics for the permutation prediction task, we use Kendall-tau and …

… Our results show state-of-the-art performance on the Public … permutation matrices is not
feasible. Thus, in this paper, we propose to approximate inference over permutation matrices to …

… For two positive integers J, L, J < L, let B be a binary matrix with row and … base matrix B and
circulant permutation matrix (CPM) of size m, we mean the code with the parity-check matrix …

… permutation matrix generating algorithm is proposed in this paper. By using the optimal
permutation matrix in matrix permutation … performance by adding appropriate matrix permutation …

… Light convolutional deep neural networks (LCNN) are attractive in resource limited
conditions for delivering high performance at low costs. Some of the state-of-the-art LCNNs in …

… permuted diagonal matrices. Compared with unstructured sparsification approach, PermDNN
eliminates the drawbacks of indexing overhead, non-heuristic compression effects and …

… permutation matrices in addition to the conventional constellation symbols. PCM works by
multiplying a permutation matrix to the singular values matrix … achieve high performance using …

… Methods based on optimal permutation Searching for the optimal permutation σ , ie for the
optimal permutation matrix P ★ , described at the beginning of Section 2, can be viewed as …

… permutation techniques to improve SpMM performance on GPUs yet preserve the CSR
representation of the sparse matrix. … Cells with high performance loss include very few samples. …

… From above tables, one can easily identify the high performance of the encryption and
decryption algorithms based on parallel computations. The throughput of encryption and …