A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.
We present the Insertion Transformer, an iterative, partially autoregressive model for sequence generation based on insertion operations. Unlike typical autoregressive models which rely on a fixed, often left-to-right ordering of the output, our approach accommodates arbitrary orderings by allowing for tokens to be ins…
We present a recurrent neural network memory that uses sparse coding to create a combinatoric encoding of sequential inputs. Using several examples, we show that the network can associate distant causes and effects in a discrete stochastic process, predict partially-observable higher-order sequences, and enable a DQN a…
We provide necessary and sufficient conditions on the derived type of a vector field distribution $\Cal V$ in order that it be locally equivalent to a partial prolongation of the contact distribution $\Cal C^{(1)}_q$, on the first order jet bundle of maps from R to Rq, q≥1. This result fully genera…
The geometric Lagrangian theory (of arbitrary order) is based on the analysis of some basic mathematical objects such as: the contact ideal, the (exact) variational sequence, the existence of Euler-Lagrange and Helmholtz-Sonin forms, etc. In this paper we give new and much simpler proofs for the whole theory using Fock…
Let $\CV$ be a vector field distribution on manifold M. We give an efficient algorithm for the construction of local coordinates on M such that $\CV$ may be locally expressed as some partial prolongation of the contact distribution $\Cal C^{(1)}_q$, on the first order jet bundle of maps from R to Rq,…
The C-spectral sequence was introduced by Vinogradov in the late Seventies as a fundamental tool for the study of algebro-geometric properties of jet spaces and differential equations. A spectral sequence arise from the contact filtration of the modules of forms on jet spaces of a fibring (or on a differential equation…
Differentiable relaxation for inferring partial orders from noisy linear data.
problem Inference of partial orders from linear data with noisy observations.
method Introducing a differentiable relaxation to model noisy linear extensions, replacing discontinuous precedence and feasibility with smooth surrogates.
result Smooth posterior that preserves partial-order semantics, supports gradient-based inference, and converges to hard likelihood.
We propose a Hodge theory for the spaces E2p,q featuring at the second step either in the Frölicher spectral sequence of an arbitrary compact complex manifold X or in the spectral sequence associated with a pair (N,F) of complementary regular holomorphic foliations on such a manifold. The main idea is to …
A convolutional sequence to sequence non-intrusive load monitoring model is proposed in this paper. Gated linear unit convolutional layers are used to extract information from the sequences of aggregate electricity consumption. Residual blocks are also introduced to refine the output of the neural network. The partiall…
We discuss intrinsic aspects of Krupka's approach to finite-order variational sequences. We give intrinsic isomorphisms of the quotient subsheaves of the short finite-order variational sequence with sheaves of forms on jet spaces of suitable order, obtaining a new finite-order (short exact) variational sequence which i…
This paper proposes a new estimation algorithm for the parameters of an HMM as to best account for the observed data. In this model, in addition to the observation sequence, we have \emph{partial} and \emph{noisy} access to the hidden state sequence as side information. This access can be seen as "partial labeling" of …
In the context of sparse recovery, it is known that most of existing regularizers such as ℓ1 suffer from some bias incurred by some leading entries (in magnitude) of the associated vector. To neutralize this bias, we propose a class of models with partial regularizers for recovering a sparse solution of a linear …
In this paper, we introduce a partial order on neighborhood equivalence classes of maximally spread essential multibranched surfaces embedded in a 3-manifold. We show that if a maximally spread essential multibranched surface is atoroidal and acylindrical, then its equivalence class is minimal with respect to the parti…
It is well known that a countable group admits a left-invariant total order if and only if it acts faithfully on R by orientation preserving homeomorphisms. Such group actions are special cases of group actions on simply connected 1-manifolds, or equivalently, actions on oriented order trees. We characterize a class of…
Study optimal liquidation strategies under partial information in high-frequency trading.
problem Optimal liquidation strategies in high-frequency trading with incomplete information.
method Modeling price formation through Hawkes processes, incorporating liquidity as a hidden Markov process, and formulating as an impulse control problem.
result Development of an algorithm to approximate optimal liquidation strategies.
Čech cohomology Hn(X) of a separable metrizable space X is defined in terms of cohomology of its nerves (or ANR neighborhoods) Pβ whereas Steenrod-Sitnikov homology Hn(X) is defined in terms of homology of compact subsets Kα⊂X. We show that one can also go vice versa: in a sense, Hn(X) can be re…
We present a new Markov chain Monte Carlo method for estimating posterior probabilities of structural features in Bayesian networks. The method draws samples from the posterior distribution of partial orders on the nodes; for each sampled partial order, the conditional probabilities of interest are computed exactly. We…
Let S be a rank-one symmetric space of non-compact type and let X be a CAT(−1) space. A well-known result by Bourdon states that if a topological embedding φ:∂∞S→∂∞X respects cross ratios, that means $\text{cr}_S( ξ_0,η_0,ξ_1,η_1)=\text{cr}_X( \varphi(ξ_0),\…
In this thesis, we show the existence of a sequence of differential operators starting with with the Dirac operator in k Clifford variables, D=(D1,...,Dk), where Di=∑jej⋅∂ij:C∞((Rn)k,§)→C∞((Rn)k,§) (§ is the spinor module). This operator is the Cauchy-Riemann operato…