Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: A Non-convex One-Pass Framework for Generalized Factorization Machine
  and Rank-One Matrix Sensing   We develop an efficient alternating framework for learning a generalized
version of Factorization Machine (gFM) on steaming data with provable
guarantees. When the instances are sampled from $d$ dimensional random Gaussian
vectors and the target second order coefficient matrix in gFM is of rank $k$,
our algorithm converges linearly, achieves $O(\epsilon)$ recovery error after
retrieving $O(k^{3}d\log(1/\epsilon))$ training instances, consumes $O(kd)$
memory in one-pass of dataset and only requires matrix-vector product
operations in each iteration. The key ingredient of our framework is a
construction of an estimation sequence endowed with a so-called Conditionally
Independent RIP condition (CI-RIP). As special cases of gFM, our framework can
be applied to symmetric or asymmetric rank-one matrix sensing problems, such as
inductive matrix completion and phase retrieval.

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The categories of this paper are: nlin
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The categories of this paper are: adap-org
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The categories of this paper are: atom-ph
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The categories of this paper are: dg-ga
4
The categories of this paper are: cond-mat
25
The categories of this paper are: patt-sol
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The categories of this paper are: solv-int
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The categories of this paper are: funct-an
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The categories of this paper are: math-ph
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The categories of this paper are: eess
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The categories of this paper are: q-bio
0
The categories of this paper are: hep-ph
3
The categories of this paper are: physics
30
The categories of this paper are: q-alg
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The categories of this paper are: cmp-lg
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The categories of this paper are: bayes-an