Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies
if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the
same subfield and year (this is the minimum needed to enter the top 1%, not the average
within it), or reaches the top citation threshold in at least one of its specific research
topics.
Citations per year, relative to Larry Rendell Larry Rendell (= 1×)
peers
Geoffrey G. Towell
Countries citing papers authored by Larry Rendell
Since
Specialization
Citations
This map shows the geographic impact of Larry Rendell's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Larry Rendell with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Larry Rendell more than expected).
This network shows the impact of papers produced by Larry Rendell. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Larry Rendell. The network helps show where Larry Rendell may publish in the future.
Co-authorship network of co-authors of Larry Rendell
This figure shows the co-authorship network connecting the top 25 collaborators of Larry Rendell.
A scholar is included among the top collaborators of Larry Rendell based on the total number of
citations received by their joint publications. Widths of edges
represent the number of papers authors have co-authored together.
Node borders
signify the number of papers an author published with Larry Rendell. Larry Rendell is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
All Works
20 of 20 papers shown
1.
Vilalta, Ricardo & Larry Rendell. (1997). Integrating Feature Construction with Multiple Classifiers in Decision Tree Induction. International Conference on Machine Learning. 394–402.1 indexed citations
2.
Rendell, Larry, et al.. (1996). Constructive induction using fragmentary knowledge. International Conference on Machine Learning. 113–121.10 indexed citations
3.
Rendell, Larry, et al.. (1996). Learning despite concept variation by finding structure in attribute-based data. International Conference on Machine Learning. 391–399.5 indexed citations
4.
Rendell, Larry, et al.. (1994). Learning hard concepts through constructive induction: framework and rationale. Conference on Learning Theory. 83–141.30 indexed citations
5.
Rendell, Larry, et al.. (1993). Improving the design of induction methods by analyzing algorithm functionality and data-based concept complexity. International Joint Conference on Artificial Intelligence. 952–959.17 indexed citations
6.
Rendell, Larry, et al.. (1993). Complex concept acquisition through directed search and feature caching. International Joint Conference on Artificial Intelligence. 946–951.14 indexed citations
Rendell, Larry, et al.. (1991). A scheme for feature construction and a comparison of empirical methods. International Joint Conference on Artificial Intelligence. 699–704.26 indexed citations
9.
Rendell, Larry, et al.. (1991). Learning structural decision trees from examples. International Joint Conference on Artificial Intelligence. 770–776.11 indexed citations
10.
Gunsch, Gregg H. & Larry Rendell. (1991). Opportunistic constructive induction. International Conference on Machine Learning. 147–152.1 indexed citations
11.
Rendell, Larry, et al.. (1990). Effective generalization of relational descriptions. National Conference on Artificial Intelligence. 875–881.6 indexed citations
12.
Matheus, Christopher J. & Larry Rendell. (1989). Constructive induction on decision trees. International Joint Conference on Artificial Intelligence. 645–650.107 indexed citations
13.
Tcheng, David, Bruce L. Lambert, Stephen C.-Y. Lu, & Larry Rendell. (1989). Building robust learning systems by combining induction and optimization. International Joint Conference on Artificial Intelligence. 806–812.34 indexed citations
14.
Rendell, Larry, et al.. (1989). Purpose and conceptual functions: a framework for concept representation in humans and machines. 13–20.2 indexed citations
15.
Mehra, Pankaj, Larry Rendell, & Benjamin W. Wah. (1989). Principled constructive induction. International Joint Conference on Artificial Intelligence. 651–656.12 indexed citations
16.
Rendell, Larry, et al.. (1987). Layered concept-learning and dynamically variable bias management. International Joint Conference on Artificial Intelligence. 308–314.37 indexed citations
Rendell, Larry. (1985). Genetic Plans and the Probabilistic Learning System: Synthesis and Results. international conference on Genetic algorithms. 60–73.18 indexed citations
19.
Rendell, Larry. (1983). A doubly layered, genetic penetrance learning system. National Conference on Artificial Intelligence. 343–347.8 indexed citations
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive
bibliographic database. While OpenAlex provides broad and valuable coverage of the global
research landscape, it—like all bibliographic datasets—has inherent limitations. These include
incomplete records, variations in author disambiguation, differences in journal indexing, and
delays in data updates. As a result, some metrics and network relationships displayed in
Rankless may not fully capture the entirety of a scholar's output or impact.