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J. Vielma

35 papers hereh-index 283.8k citations84 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • sole author3
  • first author2
  • middle author4
  • last author25

Across the 34 of 35 papers where every author was matched, so the position is known.

fields
  • math.OC29
  • stat.AP2
  • cs.LG1
  • cs.MS1
  • cs.PL1
  • stat.OT1
same name
  • J. Vielma — 2 papers, h 6

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20102026
most citedPolyhedral approximation in mixed-integer convex optimization

53 citations · 292 across the 29 of their papers we have counts for

collaborators
Showing 2018 · math.OCShow all

4 papers · 2 filters

math.OC2018

A geometric way to build strong mixed-integer programming formulations

Joey Huchette, Juan Pablo Vielma

We give an explicit geometric way to build mixed-integer programming (MIP) formulations for unions of polyhedra. The construction is simply described in terms of spanning hyperplan…

math.OC2018

Strong mixed-integer programming formulations for trained neural networks

Ross Anderson, Joey Huchette, Christian Tjandraatmadja +1

We present an ideal mixed-integer programming (MIP) formulation for a rectified linear unit (ReLU) appearing in a trained neural network. Our formulation requires a single binary v…

math.OC2018

Strong mixed-integer programming formulations for trained neural networks

Ross Anderson, Joey Huchette, Will Ma +2

We present strong mixed-integer programming (MIP) formulations for high-dimensional piecewise linear functions that correspond to trained neural networks. These formulations can be…

math.OC2018★ 38 cited

Outer Approximation With Conic Certificates For Mixed-Integer Convex Problems

Chris Coey, Miles Lubin, Juan Pablo Vielma

A mixed-integer convex (MI-convex) optimization problem is one that becomes convex when all integrality constraints are relaxed. We present a branch-and-bound LP outer approximatio…

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