Herding as a Learning System with Edge-of-Chaos Dynamics

Herding defines a deterministic dynamical system at the edge of chaos. It generates a sequence of model states and parameters by alternating parameter perturbations with state maximizations, where the sequence of states can be interpreted as "samples" from an associated MRF model. Herding differs from maximum likelihood estimation in that the sequence of parameters does not converge to a fixed point and differs from an MCMC posterior sampling approach in that the sequence of states is generated deterministically. Herding may be interpreted as a"perturb and map" method where the parameter perturbations are generated using a deterministic nonlinear dynamical system rather than randomly from a Gumbel distribution. This chapter studies the distinct statistical characteristics of the herding algorithm and shows that the fast convergence rate of the controlled moments may be attributed to edge of chaos dynamics. The herding algorithm can also be generalized to models with latent variables and to a discriminative learning setting. The perceptron cycling theorem ensures that the fast moment matching property is preserved in the more general framework

Bayesian Structure Learning for Markov Random Fields with a Spike and Slab Prior

In recent years a number of methods have been developed for automatically learning the (sparse) connectivity structure of Markov Random Fields. These methods are mostly based on L1-regularized optimization which has a number of disadvantages such as the inability to assess model uncertainty and expensive cross-validation to find the optimal regularization parameter. Moreover, the model's predictive performance may degrade dramatically with a suboptimal value of the regularization parameter (which is sometimes desirable to induce sparseness). We propose a fully Bayesian approach based on a "spike and slab" prior (similar to L0 regularization) that does not suffer from these shortcomings. We develop an approximate MCMC method combining Langevin dynamics and reversible jump MCMC to conduct inference in this model. Experiments show that the proposed model learns a good combination of the structure and parameter values without the need for separate hyper-parameter tuning. Moreover, the model's predictive performance is much more robust than L1-based methods with hyper-parameter settings that induce highly sparse model structures.Comment: Accepted in the Conference on Uncertainty in Artificial Intelligence (UAI), 201

Strong-Weak Chern-Simons-Matter Dualities from a Lattice Construction

We provide a lattice demonstration of $(2+1)$-dimensional field theory dualities relating free Dirac or Majorana fermions to strongly-interacting bosonic Chern-Simons-matter theories. Specifically, we prove the recent conjecture that $U(N)$ level-1 with $N_f$ gauged complex Wilson-Fisher scalars (where $1\le N_f\le N$) is dual to $N_f$ Dirac fermions, as well as the analogous conjecture relating $SO(N)$ theories with real Wilson-Fisher scalars to Majorana fermions for $1\le N_f\le N-2$. Furthermore, we discover new dualities that allow us to explain the interesting phase structure of the $SO(N)$ theories with $N-1$ and $N$ scalars, for all $N\ge 2$.Comment: 35 pages. v2: updated a citation. v3: minor correctio

Using Empirical Mode Decomposition (EMD) for the processing of marine MT data

Magnetotelluric (MT) method determines a frequency dependent impedance tensor using the spectra of associated time-varying horizontal electric and magnetic fields measured at the Earth’s surface. In this abstract, we present a dynamic time series analysis method dealing the non-stationary MT data to infer the impedance tensor. Most current methods to determine the spectra use Fourier transform based procedure and, therefore, assume that the signals are stationary over the record length. We introduce a new method for dealing with non-stationarity of the MT time series based upon empirical mode decomposition (EMD) method, a dynamic time series analysis method. Using EMD complicated data sets can be decomposed into a finite and small number of "intrinsic mode functions" (IMFs), which are mono-component signals and allow the calculation of physical meaningful instantaneous frequencies. EMD has no bias due to non-stationary of geomagnetic time series, since the IMFs are based entirely on signal characteristics and not on any given set of base functions such as sines and cosines in the Fourier transform or wavelets in the Wavelet transform. We use the EMD method to decompose MT data into IMFs and calculate the instantaneous frequencies and spectra to determine the impedance tensor. The method is tested in synthetic and real marine MT data sets, the obtained estimate results are reliable compared to frequently-used BIRRP processing method. Furthermore, new method has the possibility of noise visualization and filtering, which is especially important in marine applications, where noise free time segments maybe short

Time reversal invariant gapped boundaries of the double semion state

The boundary of a fractionalized topological phase can be gapped by condensing a proper set of bosonic quasiparticles. Interestingly, in the presence of a global symmetry, such a boundary can have different symmetry transformation properties. Here we present an explicit example of this kind, in the double semion state with time reversal symmetry. We find two distinct cases where the semionic excitations on the boundary can transform either as time reversal singlets or as time reversal (Kramers) doublets, depending on the coherent phase factor of the Bose condensate. The existence of these two possibilities are demonstrated using both field theory argument and exactly solvable lattice models. Furthermore, we study the domain walls between these two types of gapped boundaries and find that the application of time reversal symmetry tunnels a semion between them.Comment: 11 pages, 8 figure

End Crime with Harm? Castration for Sexual Offenders in Hong Kong

The issue of post-conviction treatment of sex offenders has been the subject of debate and changes to State legislation, particularly in respect of paedophile offences. One such treatment method is through chemical or physical castration on either a mandatory or a voluntary basis. In this regard, some States have implemented these measures for certain paedophile offences. Hong Kong (HK) has no such laws in place. Researchers such as William Winslade and his colleagues highlighted that whilst paedophilia may not be a stringently defined condition, it is one which involves a “reinforcing [pattern] of sexual behaviors,” with the result that sexual abuses of children are likely to be not only repeated, but also of increasing seriousness. As there is some evidence, albeit limited by the fact that empirical studies have been unable to use meaningful control groups or comparisons with the individuals studied prior to the treatment, that surgical castration specifically, results in a “low rate of recidivism” in sex offenders generally. This low rate might suggest that castration offers a useful mechanism for protecting children and preventing reoffending. The prospect of protecting children through prevention would therefore appear to offer justification for assessing the merits of introducing post-conviction treatment of sex offenders in Hong Kong. As such, this Article will undertake a comparison between the use of castration on post-conviction offenders from a policy and human rights perspective in the United Kingdom (UK) and California, discussing whether some form of castration should be incorporated into the HK framework. The Article argues that whilst there may be human rights implications associated with both voluntary and mandatory castration for offenders, mandatory schemes for chemical treatment may be justifiable. In a context with evidence that HK recently sought to move towards greater protection of children, despite some “disapprov[al]” among the HK public of castration as a treatment, there is a justification for considering mandatory chemical castration as a treatment of post-conviction sex offenders in the State