Eléments de l'association
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List of bibliographic references
Number of relevant bibliographic references: 10.| Ident. | Authors (with country if any) | Title |
|---|---|---|
| 000199 | Anatoli Juditsky [France] ; Fatma K L Nç Karzan [États-Unis] ; Arkadii S. Nemirovski [États-Unis] | On unified view of nullspace-type conditions for recoveries associated with general sparsity structures |
| 000493 | Anatoli Juditsky [France] ; Fatma Kilinc Karzan [États-Unis] ; Arkadii S. Nemirovski [États-Unis] | Verifiable sufficient conditions for l1 recovery of sparse signals |
| 000494 | Anatoli Juditsky [France] ; Fatma Kilinc Karzan [États-Unis] ; Arkadii S. Nemirovski [États-Unis] | Randomized First-Order algorithms for bilinear saddle point problems and their applications to l1 minimization |
| 000495 | Anatoli Juditsky [France] ; Fatma Kilinc Karzan [États-Unis] ; Arkadii S. Nemirovski [États-Unis] | Accuracy guaranties and optimal l1 recovery of sparse signals |
| 000613 | Anatoli Juditsky [France] ; Fatma Kilinc Karzan [États-Unis] ; Arkadii S. Nemirovski [États-Unis] ; Boris Polyak [Russie] | On the accuracy of l1-filtering of signals with block-sparse structure |
| 000616 | Anatoli Juditsky [France] ; Fatma Kilinc Karzan [États-Unis] ; Arkadii S. Nemirovski [États-Unis] ; Boris Polyak [Russie] | Accuracy guaranties for l1 recovery of block-sparse signals |
| 000651 | Anatoli Juditsky [France] ; Fatma Kilinc Karzan [États-Unis] ; Arkadi Nemirovski [États-Unis] | ON LOW RANK MATRIX APPROXIMATIONS WITH APPLICATIONS TO SYNTHESIS PROBLEM IN COMPRESSED SENSING |
| 000701 | Anatoli Juditsky [France] ; Fatma Kilinc Karzan [États-Unis] ; Arkadii S. Nemirovski [États-Unis] | On statistical applications of l1-recovery |
| 000704 | Anatoli Juditsky [France] ; Fatma Kilinc Karzan [États-Unis] ; Arkadii S. Nemirovski [États-Unis] | Verifiable Conditions of L1-recovery of Sparse Signals with Sign Restriction |
| 000713 | Anatoli Juditsky [France] ; Fatma Kilinc Karzan [États-Unis] ; Arkadii S. Nemirovski [États-Unis] | Verifiable sufficient conditions in compressed sensing, in Sparse Recovery Problems in High Dimensions |
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