Rajiv Khanna
25 papers · 2014–2026 · 8 conferences · across top CS/AI conferences
Achievements
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π Renaissance Researcher (5) π Interdisciplinary Bridge πΊοΈ Taxonomy Completionist (13) π§ Keyword Pioneer π Conference Polyglot (7)
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Conference Polyglot
(7)
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Academic Marathon
(10)
π
Cross-Pollinator
(14)
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Keyword Champion
(2)
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Grand Slam
π₯
Unstoppable
(11)
π
Century Club
(24)
ποΈ
Keyword Collector
(114)
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Trend Setter
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Prolific Year
(5)
Conferences
AISTATS (9)
NIPS (7)
ICLR (2)
ICML (2)
UAI (2)
AAAI (1)
COLT (1)
IJCAI (1)
Top co-authors
Research topics
Keywords
submodular optimization
(4)
greedy algorithm
(3)
feature selection
(3)
bayesian inference
(3)
kernel methods
(3)
approximate inference
(2)
column subset selection
(2)
iterative hard thresholding
(2)
greedy optimization
(2)
bayesian quadrature
(2)
generalization bound
(2)
information projection
(2)
spectral analysis
(2)
low-rank approximation
(2)
sparse optimization
(2)
nystrom method
(2)
variational inference
(2)
convergence analysis
(2)
fisher kernel
(1)
decision making
(1)
Papers
Align When They Want, Complement When They Need! Human-Centered Ensembles for Adaptive Human-AI Collaboration
AAAI 2026
The Space Complexity of Approximating Logistic Loss
NIPS 2024
A Precise Characterization of SGD Stability Using Loss Surface Geometry
ICLR 2024
Generalization Guarantees via Algorithm-dependent Rademacher Complexity
COLT 2023
Fast Feature Selection with Fairness Constraints
AISTATS 2023
Generalization Bounds using Lower Tail Exponents in Stochastic Optimizers
ICML 2022
Bayesian Coresets: Revisiting the Nonconvex Optimization Perspective
AISTATS 2021
Adversarially-Trained Deep Nets Transfer Better: Illustration on Image Classification
ICLR 2021
Geometric rates of convergence for kernel-based sampling algorithms
UAI 2021
LocalNewton: Reducing communication rounds for distributed learning
UAI 2021
Improved Guarantees and a Multiple-descent Curve for Column Subset Selection and the Nystrom Method (Extended Abstract)
IJCAI 2021
Boundary thickness and robustness in learning models
NIPS 2020
Improved guarantees and a multiple-descent curve for Column Subset Selection and the Nystrom method
NIPS 2020
Interpreting Black Box Predictions using Fisher Kernels
AISTATS 2019
Learning Sparse Distributions using Iterative Hard Thresholding
NIPS 2019
Boosting Variational Inference: an Optimization Perspective
AISTATS 2018
Boosting Black Box Variational Inference
NIPS 2018
IHT dies hard: Provable accelerated Iterative Hard Thresholding
AISTATS 2018
Information Projection and Approximate Inference for Structured Sparse Variables
AISTATS 2017
On Approximation Guarantees for Greedy Low Rank Optimization
ICML 2017
Scalable Greedy Feature Selection via Weak Submodularity
AISTATS 2017
A Unified Optimization View on Generalized Matching Pursuit and Frank-Wolfe
AISTATS 2017
Examples are not enough, learn to criticize! Criticism for Interpretability
NIPS 2016
Sparse Submodular Probabilistic PCA
AISTATS 2015
On Prior Distributions and Approximate Inference for Structured Variables
NIPS 2014