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Locality and base change along effective descent morphisms

Definition. Let $\mathcal M$ be a class of arrows in a site $\mathsf{C}$. An arrow $\pi:E\rightarrow B$ is said to be locally in $\mathcal M$ if there's a covering ${u_i:U_i\rightarrow B}$ such that $...
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54 views

Gradient descent in n-dimensional space in the context of an RBF network

I am trying to implement an algorithm to perform gradient descent in a $n$-dimensional space in the context of an RBF network. My network has 5 inputs and 1 output. It has the following Gaussian ...
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25 views

Question Janelidze and Tholen's 'Beyond Barr Exactness: Effective Descent Morphisms'

I have some questions about Janelidze and Tholen's paper Beyond Barr Exactness: Effective Descent Morphisms. First of all, they remark at the end of the introduction: Throughout this chapter $\...
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42 views

Question about limit of cosimplicial diagram associated with a sheaf

Let $F$ be a presheaf of sets on the usual topological site. Let $\left\{U_i\rightarrow U\right\}$ be covering of $U$. On the second page of Hypercovers and Simplicial Presheaves the authors write the ...
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130 views

Proposition 4.1 in Vistoli's notes on descent

Proposition 4.1 of Vistoli's notes says $\mathsf{Top}^2$ is a stack over $\mathsf{Top}$. The proof starts by looking at the fibered product $\coprod_iU_i \times _U\coprod_iU_i$, however this object ...
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49 views

Silly question about descent

Most sources say descent is defining an object over $S$ using objects over $U_i$ for some cover $\left\{ U_i \right\}$ of $S$. If I replace the covering family with a single arrow $\coprod _i U_i\...
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$\mathsf{Top}^2$ is a stack over $\mathsf{Top}$?

In section 4.1 of Vistoli's notes he starts by showing we may locally construct arrows in $\mathsf{Top}^2$, i.e arrows over $U$. Then, the author says that we can moreover do the same for spaces, ...
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32 views

Is there a nuclear norm approximation for stochastic gradient descent optimization?

I want to minimize $E$ by using stochastic gradient descent. I know that there is a sub-differential for the nuclear norm, but i want to know if is there a approximation of nuclear norm in order to ...
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53 views

Can Levenberg-Marquardt be used to find a local minimum of a function?

I've already implement an algorithm using Gradient Descent (GD) for converging to a local minimum of a function. For example the function is (using MATLAB - a=3 b=3 at this example): ...
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48 views

Show Direction of Steepest Descent is Unique

If f is a proper convex function and x is in the interior domain(f), how would one go about proving that the direction of steepest descent at x is unique? I intuitively get it, but don't get how one ...
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1answer
12 views

Parameterise Doubly Stochastic Matrices

Given the set of doubly stochastic matrices of dimension $n$, $D$, is it possible to find a continuous bijectice mapping $f: \mathbb{R}^i \rightarrow D$ for $i \leq n^2$. The motivation is to be able ...
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33 views

Asymptotic expansion using method of steepest descents

I am trying to find the first term in the asymptotic expansion of $$\frac{1}{2\pi i}\int_{c-i\infty}^{c+i\infty}\frac{1}{s^2}e^{t(s-m\sqrt{s^2-1})} ds $$ where $0<m<1$, $c<1$, as $t$ ...
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1answer
45 views

why use a small learning rate in gradient descent

I am new to neural networks and recently found out about gradient descent. Something does not sit right with me. x←x−λ∇fk(x) Why does this formula work? Wouldn'...
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33 views

(Relatively) simple applications of descent theory?

There are some questions on descent theory scattered throughout MSE and MO. The answers to these questions are generally speaking way over my head. In volume two of Borceux, there is a short chapter ...
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1answer
34 views

Reference request: convergence property of continuous gradient descent?

Does anyone know of a text that treats the problem of gradient descent from a continuous perspective instead of a discretized perspective? For example, most text investigates the numerical properties ...
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29 views

Does every Young diagram have a unique minimal major index?

Given a Young diagram, $Y_\rho$, corresponding to an irreducible complex representation $\rho$ of the symmetric group $S_n$, we can associate a set of major indices $\{ d^\rho_1,\ldots,d^\rho_{k_\rho}\...
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54 views

Can every iterative algorithm be viewed as gradient descent over some objective?

In Algorithms for Non-negative Matrix Factorization, Lee and Seung give multiplicative algorithms derived from gradient descent on the Frobenius norm to find a non-negative matrix factorization. ...
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1answer
70 views

Is there a particularly simple example of geometric descent?

I'm looking for a particularly simple and familiar example of descent in geometry or topology in order to motivate the general definition. I'm not counting the definition of the arrow category $\...
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Does faithfully flat descent work using restriction of scalars rather than extension?

Vistoli's notes on fibred categories and descent - http://homepage.sns.it/vistoli/descent.pdf - introduce (section 4.2.1) descent on modules over a commutative ring. The idea is as follows: ...
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48 views

Steepest Descent Sequence

How can I compute the first three iterates for the steepest descent sequence $f(x_1,x_2) = \frac{(x_1^2+3x_2^2)}{2}$ beginning at $x_0 = (\frac{\sqrt{3}}{2}, \frac{1}{2 \sqrt{3}})^T$ $\nabla f(x_1,...
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136 views

Unwinding descent via Barr-Beck

Let $f: U \rightarrow X$ be a faithfully flat morphism of nice schemes (quasiseparated, quasicompact, and anything else I might have forgotten). One can understand descent in quasicoherent sheaves ...
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128 views

Derivation of Steepest Descent Direction used in Line Search Methods

In the numerical optimization text I am reading, the Steepest Descent Direction was derived by considering $$ \min_{||p||_2\leq 1} p^T\nabla f(x_k) $$ This resulted in $$ p_k=-\frac{\nabla f(x_k)}...
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2answers
318 views

Gradient decent using Taylor Series

I'm reading a book about Gradient methods right now, where the author is using a Taylor series to explain/derive an equation. $$ \mathbf x_a = \mathbf x - \alpha \mathbf{ \nabla f } (\mathbf x ) $$ ...
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106 views

How does a section of a stack give a sheaf?

At nLab in the article constant stack and a few other related articles, a pattern is mentioned where a section of a constant sheaf is a locally constant function, a section of a constant stack is a ...
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46 views

When is the map “attaching irreducible components” an effective isomorphism?

Let $\mathcal C$ be a category with fiber products. We say that a morphism $X \to Y$ in $\mathcal C$ is an effective epimorphism if the sequence of sets $$ \text{Hom}(Y,S) \to \text{Hom}(X,S) \...
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36 views

Does the method of steepest decent always move in an orthogonal direction between iterations?

I understand everything, I think, about the method but the result (or requirement) that successive steps are orthogonal to each other. SO, with the formula for this algorithm as: $$\mathbf{x}_{n+1}=\...
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54 views

G-equivariant invertible sheaves on affine curves

Let $A$ be a Noetherian integral domain, and $G$ a finite group of automorphisms acting on $A$. Let $B = A^G$, the ring of invariants. The inclusion $B \hookrightarrow A$ induces a surjective morphism ...
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1answer
258 views

SGA 4.5 proof of Hilbert 90 and semilinear Galois action

In SGA 4.5's proof of Hilbert 90, proposition 1.5.2(that the inclusion $V'^G \otimes_k k' \rightarrow V'$ is an isomorphism) is deduced from faithfully flat descent as stated in 1.4.5. The way that I ...
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1answer
202 views

Using faithfully flat descent to prove representability of a functor in a simple case

Let $k$ be a field with a fixed separable closure $k_s$ and $G$ a finite type $k$-group scheme. Assume $F:(\mathrm{Sch}/k)^{opp}\rightarrow\mathrm{Set}$ is a contravariant functor whose restriction $...
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62 views

Optimization, descent direction, neccessary condition

I'm learning about nonlinear, unconstrained optimization. In my book it says that a descent direction $p_k$ must satisfy: $$p_k\nabla f(x_k)^T < 0$$ This seems to mean that $p_k$ must be obtuse to ...
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1answer
191 views

What is the difference between projected gradient descent and ordinary gradient descent?

I just read about projected gradient descent but I did not see the intuition to use Projected one instead of normal gradient descent. Would you tell me the reason and preferable situations of ...
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207 views

Intuition about multiplicative gradient descent

Suppose we want to minimize a function $f(x)$ wrt $x$, i.e., we want to solve, $$x^* = \arg \min_x f(x)$$ One method to solve such problems is gradient descent. In gradient descent, one uses the ...
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1answer
195 views

Can I check smoothness after a base-change

Let $X\to S$ be a flat morphism of noetherian schemes. I know that I can check smoothness on the geometric fibers to see whether $X\to S$ is smooth. Let $T\to S$ be a surjective morphism. Under what ...
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1answer
436 views

Machine Learning, why not use matrix multiplication instead of gradient descent?

If we want to minimize our Cost function for a given set of data, why do we use gradient descent and continually guess values until we find a min value for theta when when can just use matrix ...
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2answers
316 views

combinatorial descents finding the number of permutations with criteria

I need help with the following: Define a descent of a permutation to be $j$ when $p_{j+1} < p_j$. Then the descent set of a permutation is the set of all descents. For example, the $5$-permutation:...
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1answer
447 views

Finding descent direction of quadratic function

I have a quadratic function: $f(x) = 24x_1+14x_2+x_1x_2$ and point $x_0 = (2,10)^T$ with $f(x_0) = 208$ And the first question is "give descent direction r in $x_0$" The second question "is f convex ...
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Rate of convergence of a single-neuron Perceptron network

I'm implementing a Perceptron network which basically consists of a single neuron in a single layer, trying to learn an OR logic port (linearly separable), but using the sigmoid function as activation:...
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2answers
540 views

Solving Linearly Constrained Quadratic Programming with Coordinate Descent

Does anybody have any idea about how to solve the following problem with Coordinate Descent? \begin{align} \min &\quad \mathbf{x}^{\top}P\mathbf{x} + b^{\top}\mathbf{x}\\ \text{Subject to}& \...
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1answer
147 views

Fréchet mean between points in $\mathbb{R}^3$

Let $X$ be a set of $n$ points in $\mathbb{R}^3$ and $f_m$ be the Fréchet mean, i.e.: $$ f_m= \arg \min_{p \in M} \sum_{i=1}^n w_id^2(p,x_i) $$ where $(\mathbb{R}^3,d)$ is a complete metric space, $...
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1answer
613 views

How to prove the Energy function of a Hopfield net is monotonically decreasing?

How to prove the Energy function of a Hopfield net is monotonically decreasing? $E = -1/2 \sum_{i,j} {w_{ij}}{s_i}{s_j} + \sum_{i}^{}s_{i} \theta_i$ I'll assume a proof involves the standard ...
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212 views

Do cokernels in RingSpc automatically lead to descent?

I'm currently interested in the following result: Let $f: X \to Y$ be a fpqc morphism of schemes. Then there is an equivalence of categories between quasi-coherent sheaves on $Y$ and "descent data" ...