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Michael Jennings

dblp:40/3198 · also Michael R. Jennings · DBLP profile ↗
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2ranked-venue papers
0as first author
1since 2021 · last 2024
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Artificial intelligence and machine learning · 1 · 1 since 2021Computer networks · 1

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Theoretical computer science
1 paper
Automated reasoning and model checking · 100%
Computer networks
1 paper
Routing and switching · 38% Internet of things and sensor networks · 38% Wireless networking · 23%

Topics — the 6 heaviest of 7, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Automated reasoning and model checking › automated theorem proving
neural theorem proving
0.812024
PutnamBench: Evaluating Neural Theorem-Provers on the Putnam Mathematical Competition · NeurIPS 2024
Automated reasoning and model checking
theorem proving
0.812024
PutnamBench: Evaluating Neural Theorem-Provers on the Putnam Mathematical Competition · NeurIPS 2024
Internet of things and sensor networks › iot networks
MAC and routing integration
0.112007
Trading structure for randomness in wireless opportunistic routing · SIGCOMM 2007
Routing and switching
opportunistic routing
0.112007
Trading structure for randomness in wireless opportunistic routing · SIGCOMM 2007
Wireless networking
medium access control
0.012007
Trading structure for randomness in wireless opportunistic routing · SIGCOMM 2007
Wireless networking
spatial reuse
0.012007
Trading structure for randomness in wireless opportunistic routing · SIGCOMM 2007

Methods — techniques the papers use, named apart from their topics

symbolic theorem prover · 0.8neural theorem prover · 0.8opportunistic routing protocol design · 0.1
YearPublicationVenuePosition
2024 PutnamBench: Evaluating Neural Theorem-Provers on the Putnam Mathematical Competition
abstract
We present PutnamBench, a new multi-language benchmark for evaluating the ability of neural theorem-provers to solve competition mathematics problems. PutnamBench consists of 1692 hand-constructed formalizations of 640 theorems sourced from the William Lowell Putnam Mathematical Competition, the premier undergraduate-level mathematics competition in North America. All the problems have formalizations in Lean 4 and Isabelle; a substantial subset also has Coq formalizations. PutnamBench requires significant problem-solving ability and proficiency in a broad range of topics taught in undergraduate mathematics courses. We use PutnamBench to evaluate several established neural and symbolic theorem-provers. These approaches can only solve a handful of the PutnamBench problems, establishing the benchmark as a difficult open challenge for research on neural theorem-proving. PutnamBench is available at https://github.com/trishullab/PutnamBench.
George Tsoukalas, Jasper Lee, John Jennings, Jimmy Xin, Michelle Ding, Michael Jennings, Amitayush Thakur, Swarat Chaudhuri
NeurIPS6
2007 Trading structure for randomness in wireless opportunistic routing
abstract
Opportunistic routing is a recent technique that achieves high throughput in the face of lossy wireless links. The current opportunistic routing protocol, ExOR, ties the MAC with routing, imposing a strict schedule on routers' access to the medium. Although the scheduler delivers opportunistic gains, it misses some of the inherent features of the 802.11 MAC. For example, it prevents spatial reuse and thus may underutilize the wireless medium. It also eliminates the layering abstraction, making the protocol less amenable to extensions to alternate traffic types such as multicast.
Szymon Jakubczak, Michael Jennings, Sachin Katti, Dina Katabi
SIGCOMM2