Over any discrete memoryless channel, we build codes such that: for one, their block error probabilities and code rates scale like random codes'; two, encoding decoding complexities polar codes'. Quantitatively, constants $\pi,\rho>0$ that $\pi+2\rho<1$, construct a sequence of correction with length $N$ approaching infinity, probability $\exp(-N^\pi)$, rate $N^{-\rho}$ less than the Shannon ca...

This study was designed to explore neural evidence for the simultaneous engagement of multiple mental codes while retaining a visual object in short-term memory (STM) and, if successful, to explore the neural bases of strategic prioritization among these codes. We used multivariate pattern analysis of fMRI data to track patterns of brain activity associated with three common mental codes: visua...

We present an updated version of MegaZ-LRG (Collister et al. 2007) with photometric redshifts derived with the neural network method, ANNz as well as five other publicly available photo-z codes (HyperZ, SDSS, Le PHARE, BPZ and ZEBRA) for ∼1.5 million Luminous Red Galaxies (LRGs) in SDSS DR6. This allows us to identify how reliable codes are relative to each other if used as described in their p...

We propose an incremental strategy for learning hash functions with kernels for largescale image search. Our method is based on a two-stage classification framework that treats binary codes as intermediate variables between the feature space and the semantic space. In the first stage of classification, binary codes are considered as class labels by a set of binary SVMs; each corresponds to one ...

Consider the finite regular language Ln = {w0 | w ∈ {0, 1}, |w| ≤ n}. In [3] it was shown that while this language is accepted by a deterministic finite automaton of size O(n), any one-way quantum finite automaton (QFA) for it has size 2 . This was based on the fact that the evolution of a QFA is required to be reversible. When arbitrary intermediate measurements are allowed, this intuition bre...

This paper discusses machine learning of grammars and compilers of programming languages from samples of translation from source programs into object codes. This work is an application of incremental learning of definite clause grammars (DCGs) and syntax directed translation schema (SDTS), which is implemented in the Synapse system. The main experimental result is that Synapse synthesized a set...

We show how programming pearls can be systematically derived via fusion, followed by tupling transformations. By focusing on the elimination of intermediate data structures (fusion) followed by the elimination of redundant calls (tupling), we systematically realise both space and time efficient algorithms from naive specifications. We illustrate our approach using a well-known maximum segment s...