Matthias Boehm

Person

San Jose, CA, US

People

Patents Grantslast 30 patents

Information Patent Grant
Dynamic recompilation techniques for machine learning programs
- Patent number 10,534,590
- Issue date Jan 14, 2020
- International Business Machines Corporation
- Matthias Boehm
- G06 - COMPUTING CALCULATING COUNTING
Information Patent Grant
Global data flow optimization for machine learning programs
- Patent number 10,268,461
- Issue date Apr 23, 2019
- International Business Machines Corporation
- Matthias Boehm
- G06 - COMPUTING CALCULATING COUNTING
Information Patent Grant
Hybrid parallelization strategies for machine learning programs on...
- Patent number 10,228,922
- Issue date Mar 12, 2019
- International Business Machines Corporation
- Matthias Boehm
- G06 - COMPUTING CALCULATING COUNTING
Information Patent Grant
Pipelined approach to fused kernels for optimization of machine lea...
- Patent number 10,223,762
- Issue date Mar 5, 2019
- International Business Machines Corporation
- Arash Ashari
- G06 - COMPUTING CALCULATING COUNTING
Information Patent Grant
Runtime piggybacking of concurrent jobs in task-parallel machine le...
- Patent number 10,198,291
- Issue date Feb 5, 2019
- International Business Machines Corporation
- Matthias Boehm
- G06 - COMPUTING CALCULATING COUNTING
Information Patent Grant
Pipelined approach to fused kernels for optimization of machine lea...
- Patent number 9,972,063
- Issue date May 15, 2018
- International Business Machines Corporation
- Arash Ashari
- G06 - COMPUTING CALCULATING COUNTING
Information Patent Grant
Dynamic recompilation techniques for machine learning programs
- Patent number 9,715,373
- Issue date Jul 25, 2017
- International Business Machines Corporation
- Matthias Boehm
- G06 - COMPUTING CALCULATING COUNTING
Information Patent Grant
R-language integration with a declarative machine learning language
- Patent number 9,684,493
- Issue date Jun 20, 2017
- International Business Machines Corporation
- Matthias Boehm
- G06 - COMPUTING CALCULATING COUNTING
Information Patent Grant
Context-aware parameter estimation for forecast models
- Patent number 9,361,273
- Issue date Jun 7, 2016
- SAP SE
- Lars Dannecker
- G06 - COMPUTING CALCULATING COUNTING
Information Patent Grant
Hybrid parallelization strategies for machine learning programs on...
- Patent number 9,286,044
- Issue date Mar 15, 2016
- International Business Machines Corporation
- Matthias Boehm
- G06 - COMPUTING CALCULATING COUNTING

Patents Applicationslast 30 patents

Information Patent Application
RUNTIME PIGGYBACKING OF CONCURRENT JOBS IN TASK-PARALLEL MACHINE LE...
- Publication number 20180260246
- Publication date Sep 13, 2018
- International Business Machines Corporation
- Matthias Boehm
- G06 - COMPUTING CALCULATING COUNTING
Information Patent Application
PIPELINED APPROACH TO FUSED KERNELS FOR OPTIMIZATION OF MACHINE LEA...
- Publication number 20180211357
- Publication date Jul 26, 2018
- International Business Machines Corporation
- Arash Ashari
- G06 - COMPUTING CALCULATING COUNTING
Information Patent Application
DYNAMIC RECOMPILATION TECHNIQUES FOR MACHINE LEARNING PROGRAMS
- Publication number 20170228222
- Publication date Aug 10, 2017
- International Business Machines Corporation
- Matthias Boehm
- G06 - COMPUTING CALCULATING COUNTING
Information Patent Application
DYNAMIC RECOMPILATION TECHNIQUES FOR MACHINE LEARNING PROGRAMS
- Publication number 20170177312
- Publication date Jun 22, 2017
- International Business Machines Corporation
- Matthias Boehm
- G06 - COMPUTING CALCULATING COUNTING
Information Patent Application
GLOBAL DATA FLOW OPTIMIZATION FOR MACHINE LEARNING PROGRAMS
- Publication number 20170147943
- Publication date May 25, 2017
- International Business Machines Corporation
- Matthias Boehm
- G06 - COMPUTING CALCULATING COUNTING
Information Patent Application
PIPELINED APPROACH TO FUSED KERNELS FOR OPTIMIZATION OF MACHINE LEA...
- Publication number 20170032487
- Publication date Feb 2, 2017
- International Business Machines Corporation
- Arash Ashari
- G06 - COMPUTING CALCULATING COUNTING
Information Patent Application
HYBRID PARALLELIZATION STRATEGIES FOR MACHINE LEARNING PROGRAMS ON...
- Publication number 20160124730
- Publication date May 5, 2016
- International Business Machines Corporation
- Matthias Boehm
- G06 - COMPUTING CALCULATING COUNTING
Information Patent Application
HYBRID PARALLELIZATION STRATEGIES FOR MACHINE LEARNING PROGRAMS ON...
- Publication number 20150378696
- Publication date Dec 31, 2015
- International Business Machines Corporation
- Matthias Boehm
- G06 - COMPUTING CALCULATING COUNTING
Information Patent Application
R-LANGUAGE INTEGRATION WITH A DECLARATIVE MACHINE LEARNING LANGUAGE
- Publication number 20150347101
- Publication date Dec 3, 2015
- International Business Machines Corporation
- Matthias Boehm
- G06 - COMPUTING CALCULATING COUNTING
Information Patent Application
CONTEXT-AWARE PARAMETER ESTIMATION FOR FORECAST MODELS
- Publication number 20130024170
- Publication date Jan 24, 2013
- SAP AG
- Lars Dannecker
- G06 - COMPUTING CALCULATING COUNTING

Matthias Boehm

Person

Patents Grantslast 30 patents

Dynamic recompilation techniques for machine learning programs

Global data flow optimization for machine learning programs

Hybrid parallelization strategies for machine learning programs on...

Pipelined approach to fused kernels for optimization of machine lea...

Runtime piggybacking of concurrent jobs in task-parallel machine le...

Pipelined approach to fused kernels for optimization of machine lea...

Dynamic recompilation techniques for machine learning programs

R-language integration with a declarative machine learning language

Context-aware parameter estimation for forecast models

Hybrid parallelization strategies for machine learning programs on...

Patents Applicationslast 30 patents

RUNTIME PIGGYBACKING OF CONCURRENT JOBS IN TASK-PARALLEL MACHINE LE...

PIPELINED APPROACH TO FUSED KERNELS FOR OPTIMIZATION OF MACHINE LEA...

DYNAMIC RECOMPILATION TECHNIQUES FOR MACHINE LEARNING PROGRAMS

DYNAMIC RECOMPILATION TECHNIQUES FOR MACHINE LEARNING PROGRAMS

GLOBAL DATA FLOW OPTIMIZATION FOR MACHINE LEARNING PROGRAMS

PIPELINED APPROACH TO FUSED KERNELS FOR OPTIMIZATION OF MACHINE LEA...

HYBRID PARALLELIZATION STRATEGIES FOR MACHINE LEARNING PROGRAMS ON...

HYBRID PARALLELIZATION STRATEGIES FOR MACHINE LEARNING PROGRAMS ON...

R-LANGUAGE INTEGRATION WITH A DECLARATIVE MACHINE LEARNING LANGUAGE

CONTEXT-AWARE PARAMETER ESTIMATION FOR FORECAST MODELS